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Illinois Gaming Board
JB Pritzker • Governor
Charles Schmadeke • Chairman
Marcus D. Fruchter • Administrator
Help for Problem Gamblers
Self-Exclusion Program
In July 2002, the Illinois Gaming Board (IGB) launched a Statewide Casino Voluntary Self-Exclusion Program (SEP) for Problem Gamblers that allows persons who have determined they are problem gamblers to self-exclude themselves from all Illinois casinos. On June 28, 2019 the Sports Wagering Act was signed into law. The Sports Wagering Act requires that the Board self-exclusion program for sports wagering be incorporated into the existing self-exclusion program. Individuals already on the self-exclusion list are precluded from participation in sports wagering.
Problem Gambling Registry
In February 2018, the Illinois Gaming Board (IGB) established a voluntary, confidential Problem Gambling Registry for Video Gaming. Persons enrolled in the registry will receive regular emails providing information on problem gambling and containing links to problem gambling prevention and treatment resources available in Illinois. Individuals enrolled in the problem gambling registry may cancel their enrollments at any time. Both Illinois and out-of-state residents may enroll in the problem gambling registry.
Contact the IGB at 1-877-YOU-QUIT (1-877-968-7848) (for Illinois residents) or (312) 814-8832 (Non Illinois residents).
Department of Human Services Problem Gambling Services
The Illinois Department of Human Services, Division of Substance Use Prevention and Recovery (IDHS/SUPR) has developed the following website www.WeKnowTheFeeling.org for help, support and advice about problem gambling. The website accompanies the telephone number 1-800-GAMBLER and seeks to provide another outlet for individuals experiencing a gambling disorder and their families. People can also text ILGAMB to 53342. Each of these resources are available 24 hours a day, 7 days a week. Support specialists who operate the helpline and website are trained in evidence-based approaches to help connect callers and website users with treatment and recovery support services.
Applicable Rules
The rules regarding the Self-Exclusion Program are set forth in Sections 745-790 of the Board's Adopted Rules (86 Ill. Admin. Code 3000.745 through 3000.790).
The rules regarding the establishment of the Video Gaming Problem Gambling Registry are set forth in Section 1730 of the Board's Adopted Rules (11 Ill. Adm. Code 1800.1730).
Persons with a gambling problem may enroll in either or both of the following programs administered by the Illinois Gaming Board. The Problem Gambling Registry was created under the Video Gaming Administrative Code, but provides information that would be useful to anyone with a gambling problem.
Persons must enroll in the Self-Exclusion Program in person at various sanctioned enrollment sites throughout the state. In addition to Illinois locations, there are IGB Self-Exclusion enrollment sites in Iowa. It will take about 30 to 45 minutes to complete the enrollment process. All Self-Exclusion candidates must bring a valid driver's license or state issued identification card with them to complete the process.
Enrollment sites are not compensated by the IGB for participating in the Self-Exclusion Program and no fees are charged for enrolling in the IGB Voluntary Self-Exclusion Program for Problem Gamblers.
You may immediately enroll in the Video Gaming Problem Gambling Registry using the Problem Gambling Registry System. After you submit your information, you will receive an email containing a link you will use to verify your email address. You will not be enrolled until you verify your email address. You may use the Problem Gambling Registry System to cancel your enrollment at any time.
Self-Exclusion Enrollment Sites
Persons wishing to Self-Exclude can enroll at all of the IGB offices located at all casinos. IGB staff located at the casinos will do their best to accommodate those seeking to Self-Exclude but may ask at potential Self-Exclude persons to return at another time if conflicts arise in the performance of their other duties. An appointment is not necessary to enroll in the program at an IGB office located at a casino.
Chicago area sites Hide Sites
160 North LaSalle, Suite 300
Call 1-877-YOU-QUIT (1-877-968-7848) or (312) 814-8832 to schedule an appointment.
Associates in Behavioral Health Care
783 South Route 31
West Dundee, Illinois 60118
Call (847) 791-4384 to schedule an appointment.
Human Resources Development Institute Inc.
222 S. Jefferson Avenue
The Share Program
1776 Moon Lake Boulevard
Way Back Inn
Northern Illinois Council on Alcoholism & Substance Abuse (Nicasa)
31979 N. Fish Lake Road
Round Lake, Illinois
Renz Addiction Counseling Center
Two American Way
Elgin, Illinois
Other Illinois sites Hide Sites
Illinois Institute for Addiction Recovery
Proctor Hospital
5409 North Knoxville
Peoria, Illinois
Chestnut Health Systems
50 Northgate Industrial Dr.
Granite City, Illinois
Iroquois Mental Health Center
323 W. Mulberry Street
Watseka, Illinois 60970
Remedies Renewing Live
1908 Pierce Ct.
Belvidere, Illinois 61008
Call () to schedule an appointment.
Alpha Omega Counseling Services
123 N. Vermillion
Call (217) 274-7336 to schedule an appointment
Iowa sites Hide Sites
Substance Abuse Services Center
Dubuque, Iowa
Manchester, Iowa
ADDS Gambling Treatment Services
Suite #16
Ottumwa, Iowa
Call (641) 682-8741 ext. 301 to schedule an appointment.
1340 Mt. Pleasant Street
Burlington, Iowa
Prelude Behavioral Services
438 Southgate Avenue
3451 Easton Blvd
Center for Alcohol and Drug Services Inc.,
4869 Forest Grove Dr.,
Call (563) 322-2667 to make an appointment
Isn't it shameful to admit to having a problem with gambling? Hide Answer
No. Problem gambling is like a disease. It is not your fault or the fault of a loved one if it is contracted. But it is the responsibility of the problem/compulsive gambler to do something about it. What is shameful is to continue doing serious damage to yourself and loved ones while knowing full well that gambling is a problem. People need to be aware of the danger signals, which can give them early warning that they are susceptible to the disease.
How can I tell if I am a problem/compulsive gambler? Is there a test? Hide Answer
Gamblers Anonymous offers the following questions to anyone who feels he or she may have a gambling problem or wants to stop gambling.
Did you ever lose time from work or school due to gambling?
Has gambling ever made your home life unhappy?
Did gambling affect your reputation?
Have you ever felt remorse after gambling?
Did you ever gamble to get money with which to pay debts or otherwise solve financial difficulties?
Did gambling cause a decrease in your ambition and efficiency?
After losing did you feel you must return as soon as possible to win back your losses?
After a win did you have a strong urge to return and win more?
Did you often gamble until your last dollar was gone?
Did you ever borrow to finance your gambling?
Have you ever sold anything to finance gambling?
Were you reluctant to use "gambling money" for normal expenditures?
Did gambling make you careless of the welfare of yourself or your family?
Did you ever gamble longer than you planned?
Have you ever gambled to escape worry or trouble?
Have you ever committed or considered committing, an illegal act to finance gambling?
Did gambling cause you to have difficulty sleeping?
Do arguments, disappointments or frustrations create within you an urge to gamble?
Did you ever have the urge to celebrate any good fortune by a few hours of gambling?
Have you ever considered self-destruction or suicide as a result of your gambling?
Most compulsive gamblers will answer yes to at least seven of these questions, according to Gamblers Anonymous.
There are no dues or fees for Gamblers Anonymous. Gamblers Anonymous provdes a search for meetings in Illinois.
The National Center for Responsible Gaming has suggested mental health officials pose the following three questions to help determine if someone is at risk for developing a gambling problem:
During the past 12 months, have you become restless, irritable or anxious when trying to stop/cut down on gambling?
During the past 12 months, have you tried to keep your family and friends from knowing how much you gambled?
During the past 12 months did you have such financial trouble as a result of your gambling that you had to get help with living expenses from family, friends or welfare?
A "yes" answer to any of the questions means the person is at risk for developing a gambling problem.
How can I tell if my loved one is a problem/compulsive gambler? Hide Answer
Gam-Anon is a non-profit, self-help fellowship that offers support for family members and friends whose lives have been affected compulsive gambling. If you are living with a compulsive gambler, you will answer yes to at least six of the following questions according to Gam-Anon:
Do you find yourself constantly bothered by bill collectors?
Is the person in question often away from home for long, unexplained periods of time?
Does this person ever lose time from work due to gambling?
Do you feel that this person cannot be trusted with money?
Does the person in question faithfully promise that he or she will stop gambling, and yet gamble again and again?
Does this person ever gamble longer than he or she intended to, until the last dollar is gone?
Does this person immediately return to gambling to try to recover losses or win more?
Does this person ever gamble to get money to solve financial difficulties or have unrealistic expectations that gambling will bring the family material comfort and wealth?
Does this person borrow money to gamble with or to pay gambling debts?
Has this person's reputation ever suffered due to gambling, even to the extent of committing ill to finance gambling?
Like Gamblers Anonymous, there are Gam-Anon chapters throughout the country. Click on the Gam-Anon link below to find a listing of Gam-Anon meetings. In Illinois you may call the Gam-Anon hotline at (708) 802-0105 for assistance.
How do I Self-Exclude? Hide Answer
Persons wishing to Self-Exclude should call the nearest enrollment site to schedule an appointment.
If a person does not speak English, he or she should call 1-877-YOU-QUIT or (312) 814-8832 so arrangements can be made to have a translator present. A family member or friend who speaks English may serve as a translator.
How do I get off the Self-Exclusion List after I have enrolled? Hide Answer
The Illinois Self-Exclusion Program is for life. Removal from the list of Self-Excluded persons is very difficult. After five years a Self-Excluded person may request removal from the Self-Exclusion List. However, in order to be removed from the Self-Exclusion List, a Self-Excluded person must provide an affidavit from a licensed mental health professional who is also a certified gambling addictions counselor. The affidavit, which must be addressed to the Administrator of the Illinois Gaming Board, must attest and confirm that the licensed, certified gambling addictions counselor has determined that the Self-Excluded person no longer is a problem gambler and can gamble responsibly. Obtaining such an affidavit will be difficult.
The Administrator will take such an affidavit into consideration when deciding if a person should be removed from the Self-Exclusion List. If the submission meets the requirements for removal, there may be further investigation required by the IGB before considering the request. The IGB's legal staff may also seek public action from the five members of the Illinois Gaming Board in order to remove a Self-Excluded person from the Self-Exclusion List.
In addition, a person seeking removal from the Self-Exclusion List must provide the following:
Documentation as to treatment received for the person's gambling problem, length of treatment, and names and qualifications of treatment providers.
A written recommendation, from a qualified mental health professional who is a certified gambling counselor, as to the person's capacity to participate in gambling without adverse health and mental health risks or consequences related to gambling. "Certified gambling counselor" means an individual who has completed a specific course of study in the treatment of problem gambling and has been certified by a certification organization acceptable to the Board. Those organizations include the following: National Council on Problem Gambling, American Compulsive Gambling Counselor Certification Board and the Illinois Dept of Human Services.
Upon request of the Administrator, a written recommendation, from a second or subsequent physician or qualified mental health professional who is a certified gambling counselor, as to the self-excluded person's capacity to participate in gambling without adverse health and mental health risks or consequences related to gambling.
All information required under Section 3000.755(a), including name, address, date of birth, social security number, a copy of the person's driver's license, a physical description and a current photograph.
A statement informing the Administrator whether the person has been present at any casino gaming operations while on the Self-Exclusion List and, if so, the names of the casino operations at which the person was present and dates and times of attendance.
A waiver of liability of the Board, its agents and the State of Illinois for any damages that may arise out of any act or omission committed by the person as a consequence of his or her removal from the Self-Exclusion List, including any monetary or other damages sustained in connection with the person's renewal of any gaming activities.
A verified, written consent to the release of all of the person's medical and counseling records related to the proposed removal from the Self-Exclusion List.
Any additional information, forms, recommendations, or other materials necessary, as determined by the Administrator, to demonstrate the elimination of the mental health or medical condition underlying the person's acknowledgement that he or she has been a problem gambler and unable to gamble responsibly.
Where do I go to Self-Exclude? Hide Answer
Persons wishing to Self-Exclude may enroll at any of the enrollment sites.
If I enroll in the Illinois Gaming Board's Self-Exclusion Program, will I be excluded from only Illinois casinos and Illinois sports wagering operations? Hide Answer
No. Casinos operators in Illinois can request they be allowed to ban Illinois Gaming Board Self-Excluded persons from all their properties and operations throughout the United States. Sports wagering operations may also chose to ban Illinois Self-Excluded Persons from placing sports wagers in jurisdictions outside of Illinois. Regarding casinos, currently persons who enroll in the Illinois Gaming Board's Self-Exclusion Program are excluded from all Illinois casinos as well as all casinos and operations owned by Caesar's Entertainment Inc., Boyd Gaming Inc and Penn National Gaming Inc. Caesar's Entertainment is the largest casino company in the world and owns casinos in 14 states. Among Caesar's properties and brands are all Horseshoe, Bally's, Caesars Palace, Flamingo and Showboat casinos. Boyd Gaming owns casinos in Nevada, New Jersey, Mississippi, Illinois, Indiana, and Louisiana. Among Boyd's properties are the Blue Chip Casino in Michigan City, IN and the Borgata in Atlantic City. Penn National Gaming owns casinos and racetracks in sixteen states. Among Penn National's properties are The M Resort and Spa Casino in Las Vegas, and Argosy and Hollywood-brand casinos in Iowa, Indiana, Maine, Mississippi, Missouri, Ohio, Pennsylvania and West Virginia.
Who can Self-Exclude? Hide Answer
Anyone can Self-Exclude who has determined they are a problem or compulsive gambler and can no longer gamble responsibly.
Can I Self-Exclude my spouse or significant other from Illinois casinos and sports wagering operations? Hide Answer
No. Self-Exclusion is totally voluntary. A person cannot exclude their spouse or significant other. Those who seek Self-Exclusion must voluntarily complete the Self-Exclusion application in person at a location designated by the Illinois Gaming Board in order to be placed on the Self-Exclusion list.
My significant other told me he/she has enrolled is the IGB Self-Exclusion Program. How do I know if that's true? Hide Answer
The IGB cannot divulge the names of those on the Self-Exclusion List to spouses, significant others or employers. However, all persons who enroll in the IGB Self-Exclusion Program receive a copy of all documents that they sign as part of the enrollment process. Persons who have enrolled in the Self-Exclusion Program who have misplaced or lost copies of these documents may receive new copies only after they contact the Program Director at the IGB's Chicago Office and provide required identification. The Program Director can be reached at (312) 814-8832
My significant other has already signed up for the Illinois Gaming Board's Self-Exclusion Program and continues to gamble at the casinos and sports wager. What can I do? Hide Answer
Call the Program Director at 1-877-968-7848 or (312) 814-8832 to report your suspicions and the name of the casino or sports wagering operation where you believe a Self-Excluded person is gambling.
Does it cost anything to Self-Exclude? Hide Answer
All it costs is time. It takes about 30 to 45 minutes to enroll in the Self-Exclusion Program. Persons wishing to Self-Exclude must bring identification, such as a valid driver's license or state issued identification card. Those persons who do not speak English should make arrangements with an English-speaking friend or relative to accompany them to an enrollment site to serve as translator in order to complete the required forms.
If I enroll who will know I Self-Excluded? Hide Answer
The records generated by IGB's Self-Exclusion Program are strictly confidential. In order to facilitate the program's goals the name, Social Security number, home address, Driver's License number, date of birth and a photograph of each Self-Excluded person is shared with the state's casinos and sports wagering operations. The information provided to the Illinois Gaming Board's licensees is used only to enforce the IGB's Self-Exclusion Program.
If I Self-Exclude will the Illinois Gaming Board ever contact me? Hide Answer
All persons who Self-Exclude receive a follow up letter from the Illinois Gaming Board informing them of their SEP (Self-Excluded Person) number. The confidentiality provisions contained in the Gaming Board's Self-Exclusion Rule protects all information regarding an enrollee's application. The SEP Number is a personal identification number used to identify placement on the Self-Exclusion List.
What happens if I Self-Exclude and go into an Illinois casino or sports wagering operation? Hide Answer
The Self-Exclusion Program was created to help problem gamblers help themselves. The responsibility for staying out of Illinois casinos and sports wagering locations rests solely on the person who self excludes and not with the Illinois Gaming Board or Illinois casinos or licensed sports wagering operations. If a Self-Excluded person is found on an Illinois casino gambling or placing a sports wager, all chips, tokens and wagering slips clearly in their possession will be confiscated and any funds seized will be donated to one of three Illinois Department of Human Services designated, not-for-profit organizations created to help problem/compulsive gamblers. Those organizations include:
Illinois Council on Problem and Compulsive Gambling
Illinois Institute for AddictionRecovery
A Self-Excluded person must indicate which of the two organizations should receive such a donation at the time of their enrollment. Most importantly, a person who Self-Excludes who re-enters an Illinois casino or sports wagering location faces the distinct possibility of being placed under arrest and charged with trespassing.
I enrolled in the Self-Exclusion Program at the Outreach Foundation for Problem and Compulsive Gamblers. I selected the Outreach Foundation as the recipient of all gambling proceeds if I returned to a gambling establishment. Now that the Outreach Foundation is closed, where will those funds go? Hide Answer
On May 1, 2020 the Outreach Foundation for Problem and Compulsive Gambling shut it's doors forever. Any future Self-Exclusion seizures that designate the Outreach Foundation as a recipient will be forwarded to either the Illinois Council on Problem and Compulsive Gambling or the Illinois Institute for Addiction Recovery. Outreach Foundation designated seizures made on even calendar days will be forwarded to the Illinois Council on Problem Gambling. Outreach Foundation designated seizures on odd calendar days will be forwarded to the Illinois Institute for Addiction Recovery.
What are the responsibilities of a Self-Excluded Person? Hide Answer
After a person enrolls in the Illinois Gaming Board's Self-Exclusion Program it is their responsibility to:
Stay out of all Illinois Casinos and sports wagering locations.
Inform an Illinois Gaming Board Self-Exclusion Program Director of any change of their address
Inform an Illinois Gaming Board Self-Exclusion Program Director if they receive any brochures or letters from an Illinois casino or sports wagering operation.
After I Self-Exclude, will I continue receiving marketing materials from Illinois casinos? Hide Answer
Under the Illinois Gaming Board's Self-Exclusion Rule once a person enrolls in the Self-Exclusion Program their name must be removed from all mailing lists and marketing databases used by Illinois casinos. It may take several weeks however for a person to no longer receive mailings since some mass mailings are scheduled months in advance.
I'm on the Self-Exclusion List. Can I still go to a professional sporting event that offers sports wagering at the stadium or venue? Hide Answer
Yes. However Self-Excluded Persons may not be allowed to enter specific areas of a venue where persons may be allowed to place sports wagers.
Many problem gamblers have found that counseling or seeking help from others has helped them overcome their addiction to gambling. The Illinois Gaming Board recommends that you seek counseling.
Helpful Phone Numbers
Gambling Anonymous National Hotline: (888) GA-HELPS (888-424-3577)
Gambling Assistance Hotline: (800) 522-4700
Gambler's Anonymous (Chicago) (855) 222-5542
Gambler's Anonymous (St. Louis) (314) 647-1111
Gambler's Anonymous (Indianapolis) (317) 382-4950
Gambler's Anonymous (Wisconsin) (414) 299-0901
Gam-Anon (Illinois Hotline) (708) 802-0105
Gam-Anon (Missouri Hotline Kansas City) (816) 545-4368
Gambler's Anonymous
Gam-Anon
National Council on Problem Gambling
Illinois Alliance on Problem Gambling
Illinois Council on Problem Gambling
DHS Designated Gambling Treatment Providers
The following providers are designated Gambling Treatment Providers by the Illinois Department of Human Services Division of Alcoholism and Substance Abuse.
Board Meetings & Documents
Independent Testing Laboratories
Applicable Law & Standards
Lists of Applicants & Licensees
Board Exclusion List
Approved Games
Disciplinary Complaints
Municipalities Prohibiting Video Gaming
Rule 320 Petitions
Approved Events
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On The Day I Fell in the Water, Melissa Crabtree's third album, songs such as "Spirit Mountain" and "Daisies Talk" paint an honest picture of the muses she finds in the natural world. However it's not just her storytelling that's impressive. Crabtree has a way of incorporating a message into her songs that are both unique and exalting. The song "Bees" is complemented by the fluttering sounds of a mandolin while she addresses issues of wildlife conservation that she observes.
Then there are songs like "The Day I Fell In the Water" and "Water Canyon," which deal with how the natural world has shaped her personal growth, delving more into matters of the heart. Her combination of Folk, Americana, and Country, laced with themes of nature, is both classic and refreshing - a genuine window into the soul of a talented songwriter.
A two-song EP featuring Eliza Gilkyson on vocal harmonies. Produced by Mark Hallman.
Melissa delivers her poignant songs in a distinctly husky alto with a pleasing twang on her guitar. Smooth and delicate harmonies present her lyrics about life, relationships and politics.
Melissa Crabtree's first album, released in 2002.
A 5-song EP of all original songs produced in 2012.
In 2002, Melissa toured the country in a vegetable oil-powered van to call attention to our nation's addiction to oil.in 2002 and then toured the country in a vegetable-oil powered van to call attention to our nation's addiction to petroleum.
She produced a compilation CD about alternatives to fossil fuels that featured Julia Butterfly Hill, Tony Furtado and Julie Wolf (Ani Difranco). Her song for the compilation, "Biodiesel Van," was featured in the film "Fields of Fuel" which won Best Documentary at the Sundance Film Festival in 2008.


One of the biggest occupational hazards for someone on the benefits sides of HR is having to be the bearer of bad news. Benefits are expensive. Employers need to profit. Something has to give.
More often than not, that something is benefits. Despite your best efforts to tweak plan designs, at the end of the day, you are the one who has to tell your coworkers that their copays are increasing, their deductibles are getting higher, or that their overall benefits package is shrinking. Delivering a not-so-great benefits message is a delicate art, but it's something you have to become comfortable with if you plan on thriving in this line of work.
There are all kinds of benefits bad news, and all kinds of folks to whom you have to tell it. Before you begin crafting your communication plan, you need to understand how the bad news will affect your people.
Who will feel the impact most? Is this something that will affect everybody companywide, like when there's a senior management directive to cut HR costs? Or is it something that touches a much smaller group, like when there's a new piece of legislation that changes the way a transit flexible spending account works?
And what if the "bad news" is actually something good for most people? A new employer contribution to a highly promoted HSA plan that Medicare Part A enrollees can't take advantage of, for instance. You may have an obligation to announce bad news to everybody, but if you want to be truly helpful, you'll have to know who's really affected the most so you can craft a follow-up plan.
Too many benefits departments go radio silent after bad news is announced. That's a mistake. If you want to be smart about communicating negative changes to benefits, you'll take the time to plan general follow-up communications for the entire audience as well as individual follow-ups for the employees who'll be affected most.
This is a high-level view from 50,000 feet. You'll provide basic communication (email works well here) on the expected benefit design changes, anticipated additions or subtractions to the plans, as well as what's working well, what's not. This is a good opportunity to ask for employee input on what they like and dislike about the plan design, new/old benefits, and wish list stuff.
Way too many organizations spend all their time and resources getting a communication right only to see their efforts fall flat because they haven't taken the time to make sure the people actually delivering the message were capable and receptive to actually delivering it in the way it was designed.
Not that your team aren't professionals. They are. But they're also employees who'll be affected by the bad news too. If you don't let them grieve the loss of whatever it is they'll be losing, you risk having their unexpressed frustrations and resentments souring the message they've worked so hard to prepare.
Give your team time to be upset, and also let them know that they don't have to like the changes that have to take place. Let your team know that they can be honest about their personal feelings if the topic comes up in the course of explaining the changes.
If possible, model this tone for them in the way you discuss the changes with them. Transparency, when controlled, is healthy for employees to see and understand. Besides, you don't want to put anybody in a position where they'd have to be untruthful.
Avoid the tempation to give employees a "Bad News Sandwich". Everyone hates this kind of communication. You hate delivering it and your employees hate receiving it.
The worst communications you will ever deliver are the ones that surprise people. Simply put: Negative surprises kill culture. Just as a good manager should never deliver negative surprises during a performance review, a good benefits professional should never deliver negative surprises during open enrollment.
Great performance feedback happens in real time and on a continuous basis. Great benefits communications are similar. If you know you will have deep, or unpopular, cuts to your benefits, you need to start communicating those possibilities right away.
You should be using more direct language when describing cost and plan design changes. Also, you'll need to provide more direction to those who will be affected the most. This helps calm employee stress, and gets you out in front of possible turnover issues.
You now have the official dates and times for open enrollment on the books. You should have a solid understanding of benefit designs and costs. This is the time to begin selling the reasons of why changes need to be made.
Your communication take on a more administrative tone because all the good/bad news has been delivered many times. Focus on how employees can sign up and get the most use out of their new benefits. Any new benefits should be highlighted.
The task of open enrollment should not be emotional because you've already presented all the good/bad news. It's just a matter of paperwork from here.


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Visualization in Engineering
Visualising urban energy use: the use of LiDAR and remote sensing data in urban energy planning
Nashwan Dawood ORCID: orcid.org/0000-0002-4873-75761,
Huda Dawood1,
Sergio Rodriguez-Trejo1 &
Michael Crilly1
Visualization in Engineering volume 5, Article number: 22 (2017) Cite this article
This paper explores the potential for using remotely sensed data from a combination of commercial and open-sources, to improve the functionality, accuracy of energy-use calculations and visualisation of carbon emissions. We present a study demonstrating the use of LiDAR (Light Detection And Ranging) data and aerial imagery for a mixed-use inner urban area within the North East of England and how this can improve the quality of input data for modelling standardised energy uses and carbon emissions. We explore the scope of possible input data for both (1) building geometry and (2) building physics models from these sources.
We explain the significance of improved data accuracy for the assessment of heat-loss parameters, orientation, and shading and renewable energy micro-generation. We also highlight the limitations around the sole use of remotely sensed data and how these concerns can be partially addressed through combinations with (1) open-source property data, such as age, occupancy, tenure and (2) existing stakeholder data sets, including building services and measured performance. We set out some of the technical challenges; addressed through data approximation (considering data quality and metadata protocols) and a combination of automated or manual processing; in the use, adaptation, and transferability of this data. We elucidate how the output can be visualised and be supported by many of industry-standard CAD, GIS, and BIM software applications hence, broadening the scope for real-world applications. We demonstrate the support of commercial interest and potential drawing evidence from primary market research regarding the principal applications, functionality, and output.
In summary, we conclude on the benefits in the use of remotely sensed data for improved accuracy in energy use and carbon emission calculations, the need for semantic integration of mixed data sources and the importance of output visualisation.
Accurate alternatives for collecting information that ease geometry models creation and calculation of energy performance at individual dwelling or at neighbourhood level are needed in order to improve quality of information at disposal for architects, urban planners and authorities. A number of building physics based models have been developed in the past and some of the notable include Building Research Establishment's Housing Model for Energy Studies (Shorrock and Dunster, 1997); UK Domestic Carbon Model (Boardman et al. 2005) and Community Domestic Energy Model (Firth et al. 2010). All these models have the same energy calculation engine which is BREDEM (Building Research Establishment Domestic Energy Model) and the Standard Assessment Procedure (SAP) which is recommended by the Department Of Business Energy And Industrial Strategy (BEIS) in the UK as the main tool to underpin BREDEM for assessing and comparing energy performance of dwellings.
Accurate energy baselines for domestic buildings and neighbourhoods need that the models incorporate accurate raw data which collection can be expensive and time consuming. Generalised access to energy calculation models requires a skillset which most of the urban planners haven't yet acquired, and energy assessment usually relies on rough estimation of raw data making the energy calculation inaccurate. In this context, this paper addresses the issue of raw data availability and accuracy through the development of new processes and techniques for data collection and in particular the automated process of capturing dimensions and footprint of dwellings through the combination of OSL (Ordinance Survey and Landmap) data and deployment of LiDAR and remote sensing as means for aerial and terrestrial imagery. In addition, this captured geometrical data is further integrated with open- source and publically available data for a faster and more accurate energy calculations integrating data from available statistical sources, such as census data, deprivation and neighbourhood statistics data from ONS (Office of National Statistics), HEED (Homes Energy Efficiency Database) and EHS (English Housing Survey). This is a multi-source novel way of capturing and processing data for energy appraisal and visualisation. The remainder of this paper discuss the main technique used to capture data, dealing with errors and data cleaning, integration with other data bases and initial results from a case study.
The next section deals with remote sensing and LiDAR technology.
Remote sensing & Lidar technology
Introduction to LiDAR
LiDAR is an active remote sensing technology. It allows acquiring topographical information over surfaces at high Level of Detail (LoD), for large-scale urban areas. This data can be used for diverse aims, such as solar irradiance estimation for PV (photovoltaic) calculation (Robinson and Stone, 2004, Lukac et al., 2013), energy heating demand estimate (Tooke et al., 2014), and building type recognition and classification (Z. Lu et al., 2014) and this might represent an important input for the SAP tool calculation. The potential use of this technology is growing in line with the increased demand for accurate and updated data for energy calculation for dwellings and urban energy planners and decision makers, in a way that overcomes the limitations of plot cadastral and statistical information (Hermosilla et al., 2012).
This paper incorporates and extends on the methodology already established in Mhalas et al. (2014), where a framework that integrates visual systems, databases and a decision support system to rapidly evaluate energy performance of the dwellings is described. For this purpose, the Standard Assessment Procedure (SAP) was selected as a main element of the proof-of-concept. This paper focuses on the accuracy and availability of information that will be used for energy use using SAP as a methodology for energy calculation. Therefor the main thrust of this paper is on data gathering, cleaning, processing and use for accurate energy calculation.
The remainder of this section discusses the methods and techniques used in previous literature to pre-process, filter, noise reduction and conversion of the acquired LiDAR data and open source databases into usable object based formats in Geographical Information Systems (GIS) software tools ready to be used by energy calculation tools.
Previous literature in LiDAR data processing
Blaschke (2010) reviewed the state of the art of remote sensing technologies for Object Based Image Analysis (OBIA). The review highlighted the utilities, main limitations, as well as problems to be solved and where the main research has been focused, namely the high definition of images transformation through Fuzzy and Neural algorithm and other techniques. Tomljenovic et al. (2016) further develops the concept of use of LiDAR for 2D and 2,5D model extraction.
The use of LiDAR, within the urban built and energy related environment, has been mostly used to collect building physical features, assessment of the potential PV installation on rooftops and energy demand related studies (Lukac et al., 2013, Santos et al., 2014). Tooke et al. (2014) developed a methodology to utilise LiDAR data to aggregate a range of residential building energy and urban parameters and incorporate them with additional spatial data in order to calculate baseline estimates for energy demand for neighbouring regions within urban areas (see Fig. 1). The 3D shapes and the year of construction are incorporated within the statistically established energy performance data. Finally, both of the boundary conditions are considered, physical and environmental. The aim of the research is, based on this methodology, to systematically estimate the global energy demand for thermal uses in complete urban areas which is at the moment based on rough estimates.
Schema and workflow of Tooke et al. approach (2014)
Lukac et al. (2013, 2014) developed a methodology for determining a rating list of roofs' surfaces in relation to their solar potential and suitability for installing PV systems. LiDAR data from the urban environment has been used to obtain a 3D representation of the roofs. This data, along with irradiance historical files, have been used to estimate accurately the time dependent electricity generation from Photovoltaic Modules (PVMs) and the solar inverter, taking into consideration the non-linearity of the process and the accurate shadowing calculation inferred by the topological map created for the whole of urban area. These estimates are then compared with measurements obtained from a monitored PV plant. Jochem et al., 2009, Heinzel and Koch, 2011, Mongus and Zalik, 2012 presented methodology for the pre-processing of the LiDAR data using State of the Art classification methods. The obtained cloud points from LiDAR capture are converted into the urban elements and buildings' rooftops surfaces, with a twofold objective; firstly, to be able to accurately estimate the slopes and orientation of the PVM on the rooftops, and secondly, to calculate the instant shadowing during a whole year period (Lukac et al., 2013, Yuan et al., 2011). Lu et al. (2014) developed a methodology to generate a building information accurate geodatabase, which solves the limitations of obtaining data from parcel datasets that are often not reliable and up to date. Apart from the directly inferred geometrical data, the approach eases building and boundary area classification. The process includes three main tasks: (1) to delineate the boundaries of buildings and elements within the data, (2) to separate building data and (3) to classify the buildings into pre-established types.
It was concluded from previous efforts and approaches in building and neighbourhood energy modelling, that integration of information coming from various data sources is one of the greatest obstacles to tackle for application of LiDAR data in urban and city planning and operation. There is a challenge of managing urban change within the paradigm of the 'information city' (Kraemer & King 1988). Municipalities and their partners require a supporting information infrastructure that supports a broad range of urban stakeholders to mutually understand and reinforce geophysical communities within urban neighbourhoods and localities (Doheny-Farina 1996). The city map and urban model remain the most intuitive ways of structuring and accessing this urban information.
Appropriate and accurate data is crucial for understanding the viability of substantive urban energy systems and decision-making procedural systems that manage the urban system (Grossmann & Watt 1992). In effect, there are complementary requirements from both technical and non-expert urban stakeholders in the use of urban energy information, its collection, analysis, sharing, and visualisation. Here, there is real potential for LiDAR data collected remotely at neighbourhood or city scale to simultaneously contribute to both, the technical and political decision-making requirements for better data. Initially it is ideal for information directly relating to building geometry. This geometry or 'property-based' data can be the basis for integration with wider and 'softer' aspects of urban planning and sustainability.
As summary from the previous literature review, it is possible to generate an estimation of an individual property energy use based on the attributes of the building supported, but not limited to cadastral plots (age / method of construction, geometry and services) and 'standardised' behaviour of the typical occupants. It is these property attributes that are well suited to the integration of LiDAR data on geometry with other open-source and publically available data sets that record the building performance characteristics. For example, the use of open-source database on the age of construction of the property, the use of stakeholders' own asset management database, systems upgrades to social housing as part of 'decent homes programme'.
This research presents a case study using a similar approach to the techniques demonstrated in Tooke et al. (2014). It presents the process to collect and pre-process data with the aim of estimating more accurately, the global energy demand for thermal uses in complete urban areas. Unlike in the Tooke's approach, the calculation for the baseline estimates of energy demand is based on SAP methodology shown in Mhalas et al. (2014). Database and assumptions are adapted to the case study. Visualisation and integration of the generated data offers a wider range of possibilities compared to the aforementioned approaches, combining and merging the results of the model with open source GoogleMaps and GoogleEarth. Figure 2 shows the workflow of the proposed approach for estimating Energy Demand, integrating different data sources.
Baseline Energy Performance Assessment procees map
The next section introduces the case study that was conducted in this research to demonstrate the techniques and methodologies used to process data for energy calculation.
Capturing geometry data: a case study
The objective of this section is to introduce a real life case study to demonstrate the procedure of capturing, processing and using LiDAR information. A case study is selected in the inner area of west end of Newcastle upon-Tyne in the UK. This case study was part of SEMANCO (Semantic Tools for Carbon Reduction in Urban Planning), a European project co-funded by the European Commission within the 7th Framework Programme (http://semanco-project.eu/). The case study is based on an area which contains a variety of housing typologies, including significant multi-story and multi-occupancy properties for a mix of different ownership patterns and tenures. The research project presented in this paper commissioned the LiDAR scanning of the project area for the purpose of calculating energy rating and ways in which these ratings can be improved through a more informed refurbishment programmes. The rationale was to overcome some of the costs and technical limitations of existing two-dimensional spatial data sets; for example, Ordnance Survey Landline / Master map that only held building ground floor footprints and no accurate building heights. Moreover, for the purpose of energy calculation and to augment the geometric information from LiDAR. This research has investigated the potential use of a variety of publically accessible and open-source data sets such as age of property, construction methods, type and age of boilers, etc.
The key intention for LiDAR data use was to support the estimation of urban energy use where there is a requirement for a high degree of accuracy in the building geometry. In addition, the commissioned LiDAR data included the necessary permission to integrate it with other data sets as part of an online energy modelling and decision-support tool. The rights to share this data and demonstrate the potential functionality when it linked to other data sets, is one of the initial outputs of this research work. Effectively, it allowed the research team to maintain an open-ended approach to the use and adaptation of the data set without being time-limited or legally restricted to the scope of use.
Data specification and data collection
The supply and collection of the LiDAR data was performed by a professional commercial provider (Blue Sky Company PLC). However, many factors and issues are realised regarding the specification of the data collection. Most significantly is the lack of any standard specification for the format, resolution and cleaning of the data, the following section discusses this.
Data conversion and input
The provided data used CityGML (City Geography Markup Language) and COLLADA (COLLAborative Design Activity) formats that are readable within many different standard software packages. Inner city is surveyed over a square kilometre using two separate scans that provided a terrain model and 'partially' auto-rectified structures. Typically, LiDAR data contained more than required details of specification in certain areas and significant gaps regarding surface materials and varied dimensions of these solid / opaque surfaces. There are some recent demonstrations of the application around the detail available and transferring or 'tracing' (Kimpton et al. 2010) CAD polylines over a polygon surface model / point cloud data. This is effectively a manual task to reduce the level of detail within the model. It turns a set of point cloud data into closed polygons – polygons with properties suitable for adding attributes and for visualisation. A similar approach is required for the neighbourhood scale to make the data usable for the purpose of estimating the energy use for individual properties.
The process of inferring 2D and 2,5D-classified information from the point cloud data through processing is time consuming and depends greatly on technical skills. However, the use of software such as ArcGIS (a complete, cloud based mapping platform) can automate these tasks easily through the implementation as modules, to obtain the features as the building footprint, height and shape. However, there is sparse development of this semi-automatic data processing, which depends a great deal on the density of points for the images at disposal. According to Henn et al. (2013) in the UK, the density is 0.5 points/m2, 1 points/m2 for Germany and 8 points/m2 for the Netherlands. In the latest years, resolution available data has improved considerably, but at the time the survey was done, the density of data at disposal was at first instance not enough to conduct accurate identification. That can be the case in a majority of cases. Combination of usual 5 × 5 m2 resolution files with LiDAR 4 points/ m2, as for the conducted survey in the case study, means a significant improvement in accuracy and data consistency. Ultimately, the data has two significant geometry values that need to be maintained as input measurements into a Reduced data Standard Assessment Procedure (RdSAP) or estimated SAP calculation process as the normal UK energy model. The input geometry is (a) the shape of the property; measured as the gross external footprint of the individual dwelling unit; and (b) the height of the property. Together, these input parameters allow an accurate calculation of heat-loss parameters around the extent of internal heated living space relative to the exposed surface areas as made up from the ground floor, external walls and roof. While there are limited opportunities for changing the shape (simplifying) and size (reducing) of homes to affect the heat loss parameters (Friedman 2005), building fabric interventions (typically internal or external insulation) can improve the thermal efficiency of specific building elements to reduce the heat loss. In most cases, improvement work to the building fabric will also be dependent upon the same geometry in terms of cost of treatment per square metre. Further interventions relate to possible upgrades to building services or the provision and connection to renewable and / or decentralized energy systems. These can likewise be attached as attributes to the property-based data that is consistent with similar scoping and qualitative assessments of stakeholder requirements (National Refurbishment Centre 2012) and those responsible for property management and maintenance, there is a practical focus on cost-effective and technically trusted approaches to refurbishment that requires good evidence base on accurate data.
In order to reach the point of using accurate building geometry data we need to identify any significant errors inherent within the original format of the commercially provided data and implement some data editing. Most of the errors reflect to inconsistencies of the polygons, differences to cadastral existing information, vegetation and unrecorded elements and structures. Figure 3 shows key steps in data handling processes.
Key steps in data handling processes in Lukač et al. approach (2013)
Errors within data collection
To acquire useful data sets for energy monitoring, several types of initial data errors needed to be dealt with in advance. These errors relates to almost exclusively issues of 'bad geometry' arising from a combination of the angle of scanning of the terrain and properties together with the level of 'noise' within the LiDAR data. The 'noise' included errors from building overhangs, shadows, trees / vegetation and became more pronounced in areas where there were more complex geometries and structures. Figure 4 highlights some of LiDAR data issues and errors.
Highlighting the initial LiDAR data errors
The best strategy in dealing with the various geometry errors is to create two separate data sets that hold discrete input data. The first deals with building footprints and the second with building heights. This strategy has proven most effective in a more complex process. Bremer et al. (2016) showed a process for which data is processed in three steps, from coarse Digital Surface Model (DSM) to fine DSM and making use of the close range domain given by the fine Digital Terrain Model (DTM) and the LiDAR points cloud. This information is checked against CityGML to obtain the final polygonal information in a 2.5D data file. The approach taken in this case study consists of checking the polygonal information from both 2D footprint and 3D height information, check for inconsistencies and solve clashes of information. Figure 5 depict a flow chart for cross data and inconstancies correcting and Fig. 6 shows an example of data error correction.
Flowchart of the process for correcting polygonal inconsistencies
Examples of correction of data errors
Data cleaning and editing
The first step in handling data is to pre-treat data by eliminating any basic errors/ outliers. Editing is carried out using the edit functions within ESRI's ArcGIS (see Fig. 6).
Overlapping polygons in the commercial data set are cleared of errors as they represent two properties occupying the same building footprint. These are merged and then split along an estimated property boundary. Furthermore, there were issues with sections such as disconnected polygons or 'gaps' in between terrace properties. These had their vertices snapped to match.
There are several instances of vertices existing within polygons that seemingly picked up variations in roof structures, chimneys / ventilation or in some instances in larger multi occupancy properties and non-residential units mechanical and engineering services plant on the roof. These are merged into single polygons with all extraneous vertices deleted. The result represents an accurate footprint data set.
Identifying individual properties
The next step was to separate the contiguous polygons / structures into individual properties. It is useful that the LiDAR data is effective in picking up changes in external building heights. In an area of exaggerated topography in the west end of Newcastle where contiguous properties / terraced housing step up and down the slope, this suggests division between properties. However, in looking at the details, it failed to make a distinction between property boundaries because this boundary is in reality the thickness of a party wall between the individual properties. The change in roof heights coincided with the end (or in some instances the roof overlap) of the party wall and not the middle of the party wall. This becomes apparent when rear extensions have to be attributed to a particular property polygon. This could only be corrected manually using 'best-guess' information (Fig. 7) based on equidistant polygons to create properties of equal sizes as a typical property typology or using external information to property boundaries.
Data editing to create individual property polygons
It is accepted that additional errors are re-introduced at each of these discrete stages within data cleaning and editing. Maintaining two separate data sets holding the footprint and height details separately is the best strategy to reduce the number of stages in data handling and thus reducing the potential of re-introducing any new errors when handling data.
Integration with other data sets
Thinking around the value of city models is rapidly changing in response to the power of computing but more significantly, the quantum of big data that now exists digitally.
We are entering into a world where everything is data. Planning has to deal with the scope of different sources of supporting evidence each using a variety of methodologies. There has to be an understanding of limits, unpredictability and allied to this are the procedural issues around irrationality, objectivity and political / cultural perceptions and definitions of qualitative aspects of behaviour, knowledge, attitudes and perceptions. Maps are clearly a useful way to explore data. Nonetheless, ultimately they are didactic tools. They are abstractions of reality and are designed primarily for exploration and understanding at strategic scales and early stages of decision-making. They will contain errors and have to be treated as tools for understanding rather than predicting energy usage.
Porter & Neale (2000) acknowledged the development of the 'map' or 'model' from physical to digital, a paradigm shift in urban design and planning '… that hold(s) the potential for allowing the designer to move directly from concept to full scale construction'. In order to achieve this, the development of new methodologies to support the analysis and integration of large data sets has to be implemented (Aiden & Michel 2013). Real 'big data' can be considered a replacement for intuition or guesswork where there are strategies in place for harvesting and mining every possible source (Baumgartner et al. 2012).
LiDAR data use for energy performance evaluation with SAP engine
Precise image data and aerial imagery is needed in order to conduct accurate neighbourhood energy performance evaluation. As well, use of published databases such as Homes Energy Efficiency Database (HEED), household surveys such as English House Condition Survey (EHCS), census and the Office of National Statistics (ONS) are used as data sources for input for the core SAP calculation engine as detailed in Mhalas et al. (2014).
Basing on this research, we realised that one major condition for the city model development, i.e. Newcastle Cruddas Park building areas (Fig. 10) included in the use case, was that it should support the demonstration of the baseline energy modelling SAP based software tool, with the variety of building and dwelling archetypes. To do that, accurate individual geometries of buildings needed to be put in place, in order to allow correct identification when geo-referencing and establishing links to the cadastral and other Database information sources. In the first instance, due to the resolution and also potentially the nature of the conveyed drive-by surveys, available data was not sufficiently consistent for these purposes, raising concerns related to the data processing regime and date of data capture, i.e. a number of buildings were missing from the map; the height of some buildings appeared to be updated in the MIMAS (2012); some of the extruded 3D blocks did not correspond to buildings at all. Additionally knowledge of the site, images and visual inspection analysis allowed the recognition of other discrepancies, which meant a barrier for the definition of the energy performance map.
The selected process followed to generate and classify the individual building geometries according to the predefined archetypes is found in the IDEF0 map (Fig. 8), evolved from previous research found in Mhalas et al. (2014). The use of LiDAR was of help in resolving the aforementioned definition barriers in the Geometry and Physics components in Fig. 7. It allows the correct identification of individual buildings and a georeferenced location of them, granting integration of the COLLADA files with CityGML and open-source resources as Google Earth Pro. Both SHP vector files and CityGML files are superimposed on aerial map adding a layer to the open-sourced one.
Dwelling Objects Creation
This precise imagery serves as input for the SAP sub-models for the specific building. This consists of extracting information for footprint, floor height, exposed perimeter wall area, and roof-area as well as opaque and window area and materials (U-values). Once the LiDAR file for a specific neighbourhood is in place, we use OS MasterMap layer and OS MasterMapTopography Layer to identify the buildings, and Visual Basic for Applications (VBA) to add information related to building physics and usage. ArcGIS features attribute replication for different buildings. Once the different buildings units and attributes have been defined ArcGIS developer allows SAP algorithms to be formulated into calculation tools, which will result in energy demand, heating and cooling demand, electricity demand, PV and Thermal solar generation. The process to obtain neighbourhood Baseline Energy Performance Assessment integrating the LiDAR data is shown in Fig. 2.
Visualisation of this data can be either be obtained with the aerial survey map, creating tailored layers to show the different output values, or integrate them into open-source platform layers as GoogleMaps or GoogleEarth. Both options need to create the layers using the KML layer creation. In that way visualisation of neighbourhood extended attributes becomes available for the platform users, and becomes a valuable source of information for urban planners, architects, and public services.
Stakeholder data and user-defined mapping
Big data tends to have veracity as well as volume, velocity, and variety. One of the key support tasks is to organise, structure and make sense of data. This is generally accomplished using one or more of the industry standard software packages, ArcGIS, AutoCAD, Sketchup and to a lesser degree, Google Earth. Additionally, there is an open-source mapping software and data, for example in the ESRI sponsored crowd-sourced mapping (Medeiros, 2013). Building energy data is just another element of this big data. Building energy use and carbon emissions have to be understood in the wider policy context and the complexity of the real world. There is a requirement to provide for users the ability to export, import, and connect with their own datasets to build on the functionality of the basic building geometry. Moreover, the significance of having remotely sensed data is that it provides accurate building geometry and other information. While initially, this geometry has value as input data for the calculation of the energy efficiency of buildings, this can be modified to incorporate a rage of additional functionalities when data is shared online and is linked to the individual property addresses for a more accurate measurement. For example, for the calculation of property refurbishment and renovation costs, building geometry is linked to a cost database or cost estimations.
Furthermore, the availability of an open-source three-dimensional data is both limited and controlled and remarkably the same case study area of Newcastle in represented in Google Earth and effectively uses the same data from the same commercial supplier (see Figs. 9 and 10). Yet the functionality of this is limited to basic visualisation and the virtual exploration of the urban environment. The export functions, if any, are limited to two-dimensional aerial imagery, creating a level of frustration in achieving the level of accuracy, which is available through open-source data compared to the knowledge of the existence of accurate geometry. Yet this data is still currently just a collection of shapes without any property specific tagging. However, looking beyond the visualisation of the data are extractable geometry models that can be used for a variety of purposes, including acting as input data for more detailed urban design and architectural modelling.
Process for Data integration into GoogleEarth KML layer
Data visualization integration into GoogleEarth KML layer
Discussion on the importance of visualising energy data and future work
Urban planning and regeneration is complex as it brings together a broad range of stakeholders, as a mix of technical professionals and many different non-expert stakeholders that have their own personal and organizational experiences. Urban planning and management has become a two-way educational mutual learning process (Wals, 1996) that have connections between many consultation / participation exercises. These urban planning processes require the development of evidence base and information provision that is accessible and understandable to the broad scope of project stakeholders and in particular visual energy use. Indeed, Castells (2000) suggested that the appropriate sharing of urban data assists with the reform and legitimization of local democracy and governance. Data, including energy data, with all of its errors is best shared in a manner that is accessible to multiple stakeholders and is understandable to non-technical users, extractable and editable for technical users.
The SEMANCO project reported in this paper has provided an online platform that provides access to widely dispersed energy related data about cities stored by many organisations. Thus, the platform supports improved energy analysis based on the assessment of existing data rather than estimates. This is performed using semantic data modelling that uses information stored in different places with different formats to create a multi-level energy model of an urban area. This can be further used to analyse the energy performance of individual buildings, neighbourhoods, districts and regions. Figure 11 shows a screen shot of the developed SEMANTIC tool for the Urban Energy Model.
Developed SEMANTIC tool for Urban Energy Model
The SEMANCO platform includes a set of tools to visualise and analyse a city's energy data. The visualisation combines interactive 3D models, tables and diagrams to display energy related data. Madrazo et al. (2013) stressed the importance of the visual three-dimensional interface as a common language for a range of stakeholders becomes more apparent.
Although it is a significant way short of BIM standards, this is potentially the next step in the use of LiDAR information. Format and specifications in line with Construction Operations Building Information Exchange (COBie) and can be useful at the earliest stages of a design or construction plan of works. At present ISO 1006-2 sets the specification standards for ICT in construction projects and includes a detailed ontology for construction and building elements. This standard also sets out the design responsibilities between different professional stakeholders and the minimum requirements for technical / digital information change between the professionals. The standards overlap with COBie standards for data exchange, which sets out the specification of element properties in the form of an industry standard data language with specification properties. For the SEMANCO project, strategies are consigned to convert LiDAR datasets into accurate urban consistent information data to be used in COBie compliant BIM tools as well as specific energy related information fields have been merged to obtain an energy related ontology (Corrado et al., 2015). This is achieved by creating a formal vocabulary according to the Ontology Web Language specifications to assess the energy performance of an urban area.
As an increasing range of software packages use COBie standards for data input and integration, the challenge is to allow the use of remotely sensed LiDAR data on building geometry to be useful and timesaving as input data into these design software packages. Here the best versions are mostly automated from Revit or similar SOLIBRI compliance checking software. When remotely sensed data can be used with confidence at an early project stage and form part of the initial information exchange it will have significant new functionality. It has to be remembered that while most design packages and protocols are intended for new construction, around 80% of all construction projects still include existing structures for renovation, refurbishment, adaptation, or conversion (Itard & Meijer 2009). An accurate representation of existing structures with a usable database containing the attributes and parameters of these structures will be hugely valuable addition to the initial business planning stages of many urban planning and regeneration projects.
It is also valuable to address compatibility of this methodology to parallel efforts in the direction of the W3C and Linked Building Data group to generate city models integrating data from disparate data sources such as LiDAR, photogrammetry and other survey methods considering OWL (Web Ontology Language). This points out the direction to follow, going beyond the building bound COBie and IFC models.
This paper presents a methodology to integrate remote sensing methodology and LiDAR techniques to visualise and calculate urban energy use in neighbourhoods, making use of proprietary and open source software tools. The paper emphasises the process to improve consistency of data for the assessment of energy use and calculation in urban settings and analyses the different barriers and problems raised in the undertaken research and solutions to them. The paper highlights the limitations around the current ways in which neighbourhood energy analysis and calculations are conducted and how these can be addressed through combinations with open-source property data and existing stakeholder data sets, including building services and measured performance. The paper shows how remote sensing data and LiDAR information can be captured, cleaned, processed and used.
This paper puts the thrust in ways to ease city models generation integrating LiDAR survey maps, especially considering neighbourhood energy analysis and benchmarking. In sum, the process improves the aspects of the model generation, process, analysis and visualisation, making use of widespread cloud based software tools. Unlike existing approaches, the possibilities open by the research shown in this paper enhances the use and handling of neighbourhood energy analysis and the integration with other visualisation tools enables not proficient users to access tailored and versatile information.
BIM:
BREDEM:
Building research establishment domestic energy model
CAD:
CityGML:
City geography markup language
COBie:
Construction operations building information exchange
COLLADA:
COLLAborative design activity
DSM:
Digital surface model
DTM:
GIS :
Geographical information system
LiDAR:
Light detection and ranging
LoD:
OBIA:
Object based image analysis
Photovoltaic, 4
PVMs:
Photovoltaic modules, 5
RdSAP:
Reduced data standard assessment procedure
Standard assessment procedure
SEMANCO:
Semantic tools for carbon reduction in urban planning
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Wals, AEJ. (1996). Back-alley sustainability and the role of environmental education. Local Environment, 1(3), 299–316.
Yuan, H, Dai, Y, Xiao, Z, Ji, D, Shangguan, W. (2011). Reprocessing the MODIS leaf area index products for land surface and climate modelling. Remote Sensing of Environment, 115(5).
This paper is based on applied semantic modelling research work undertaken as part of the SEMANCO project. SEMANCO is supported by the Seventh Framework Programme 'ICT for Energy Systems' 2011-2014, under the grant agreement Number 287534.
The data can be shared and will be available on request.
Center for Construction Innovation and Research, Teesside University, Middlesbrough, TS1 3BA, UK
Nashwan Dawood
, Huda Dawood
, Sergio Rodriguez-Trejo
& Michael Crilly
Search for Nashwan Dawood in:
Search for Huda Dawood in:
Search for Sergio Rodriguez-Trejo in:
Search for Michael Crilly in:
Prof. Dawood: lead the research work into the visualisation and development of the research methodology. He has wrote the theoretical contents and research approaches. Dr. Huda Dawood, Dr. Sergio Rodriguez-Trejo and Dr. Michael Crilly contributed to the development and writing up of the visualisation model. Dr. Sergio Rodriguez-Trejo contributed to the theoretical framework and the energy engine part. All authors read and approved the final manuscript.
Correspondence to Nashwan Dawood.
The work did not involve any human subjects' participation or animal experiments and therefore this is 'Not Applicable'.
There are no financial or non-financial interests by the authors to declare.
Dawood, N., Dawood, H., Rodriguez-Trejo, S. et al. Visualising urban energy use: the use of LiDAR and remote sensing data in urban energy planning. Vis. in Eng. 5, 22 (2017) doi:10.1186/s40327-017-0060-3

redpajama_set_name: RedPajamaCommonCrawl


text:
Man kills mother, sister in Medchal to pay off his gambling debts
By Newsmeter NetworkPublished on 30 Nov 2020 10:15 AM GMT
Hyderabad: A man who had lost heavily in cricket betting and incurred huge debts killed his mother and sister for money to pay off his debts in Hyderabad's Medchal.
P. Sainath Reddy had lost huge amounts in cricket betting. He hatched a plan to kill the two women hoping to inherit the family property, sell it, and clear his debts with the money. He laced their food with pesticide. After battling for their lives for more than a week, Sunitha and her daughter Anusha died while undergoing treatment.
Sainath would have got away with his plan but his relatives and villagers grew suspicious and alerted the police just before the final rites of the two women. The cops swung into action and questioned Sainath who confessed to the crime.
The Reddy family is from Ravalkole village in Medchal. Sainath's father, Palli Prabhakar Reddy, passed away a few years ago, leaving Sainath, his mother Sunitha, and sister Anusha. Sainath was pursuing MTech while also working for a private firm.
After his father's death, he got involved in betting and spent huge amounts. When he came to know that his father's insurance amount was lying in his mother's bank account, he withdrew the money without her knowledge and spent it on betting. However, he kept losing money. He had also stolen his mother's gold jewellery and sold them to support his habit.
Gradually, he slipped into a financial crisis. To get out of this, he hatched a plan to kill his family. He mixed pesticide in their food and when they became unconscious after consuming it, he admitted them to a hospital saying they had food poisoning. Sunitha and Anusha died within a week.
The police found that Sainath was using mobile apps for cricket betting and that he had also availed loans from agencies that operated through mobile apps.


text:
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Friends of Leadburn Community Woodland submitted a request to purchase 9.4 hectares of land at Leadburn, next to Leadburn Community Woodland. FLCW proposed to increase the variety of walks available from the community woodland and to open up views to the south by removing many existing conifers. The cleared area was to intended to be restored as a raised bog.


Eduardo Rodriguez was chased after recording only 10 outs (3.1-6-5-3-4, 78) and the Red Sox hitters failed to deliver twice in the clutch, leaving seven men on base in the first four innings.
Trailing 5-1 in the fourth, the Red Sox loaded the bases after two were out. Christian Vazquez walked, Jackie Bradley singled to center, and Mookie Betts walked. Andrew Benintendi - representing the possible tying run - drove the ball towards the left field wall, but Jake Marisnick ran over from center and made a superb catch along the wall on the run.
Xander Bogaerts (3-for-5) homered in the fifth. He had also knocked in Boston's first run with a single to left that scored Betts. The Red Sox went in order in the sixth and seventh, and Mitch Moreland's double was wasted in the eighth.
Facing Roberto Osuna in the ninth, Blake Swihart singled to left. With one out, Betts walked. Both runners advanced on a wild pitch before Benintendi's groundball single into left scored Swihart and sent Betts to third.
With visions of a walkoff dong dancing in their heads, the Faithful roared for J.D. Martinez. He fouled off two fastballs before swinging at a low changeup. He grounded it to shortstop Carlos Correa, who started a 6-4-3 double play that ended the game, and left JDM with his first 0-for-5 collar of the season.
The Red Sox's magic numbers: Clinch a playoff spot: 3. Clinch the AL East: 13.
[W]henever he's ready he'll be ready. ... As far as throwing ... we'll talk about it [on Saturday] and map it out and hopefully it's sooner rather than later, that he'll be back in a few days.
In his last 11 games, Barnes has allowed 10 runs and four homers in 10.1 innings.
While the postseason trend is more innings from the bullpen and fewer from the starters, the Red Sox may have to go deeper with their starters than other teams if the bullpen doesn't start locking down more zeroes.
At the start of August, the Red Sox bullpen had a 3.34 ERA, sixth best in the majors. Since the beginning of August, it's 4.11, 18th in the majors. And since Aug. 24, it's 5.22, 24th in the majors.
Attention! This is WEEI's gloom-and-doom train, making daily stops through the first week of October. All aboard!
The Red Sox are 97-45 with 20 games remaining. The 1912 team holds the franchise's win record: 105-47-2.


MIAMI -- It's unlikely any comprehensive immigration bill will be passed if its creation is left up to Congress, according to the former head of U.S. Citizenship and Immigration Services.
Emilio T. Gonzalez, who stepped down in April and subsequently took the helm at the U.S. subsidiary of Spanish technology firm Indra Sistemas S.A., told The Associated Press that immigration is just too complex and politically charged. He also said he doesn't expect such legislation to emerge early in the next presidential administration.
"Immigration is very difficult, and it's very complex," Gonzalez explained. "You've got to get dirty, and you're going to get beat up. I can't imagine somebody burning political capital in a honeymoon period tackling immigration."
Gonzalez, a native of Cuba who was raised in Florida and has long made Miami his home, looked relaxed in a pink guayabera shirt, as he spoke in an interview Tuesday from his offices at Indra USA about the future of immigration policy. Gone are the days of government suits and being attacked for not doing enough - or doing too much - for immigrants.
He said, ultimately, the nation's president will have to be the one to lead the charge on new immigration legislation.
"I think this will get done when it comes from on high - that is to say when a president really puts it on the line and basically crafts the bill and says: 'Congress, this is what I want,'" Gonzalez told AP from his offices in Miami's financial district.
Gonzalez lamented that the loudest voices in the immigration debate remain on the extremes - either in favor of letting everyone in or trying to keep everyone out while ignoring the roughly 12 million already here illegally.
Gonzalez called it "logistically impossible" to send all illegal immigrants home.
He said he hoped a Senate bill last year that required illegal immigrants pay heavy fines and go to the back of the line in requesting citizenship would help assuage concerns about an amnesty, but the bill failed by 14 votes. Two-thirds of Republican senators voted against it.
"Congress essentially said, 'you haven't done enough on interior enforcement,'" Gonzalez said, adding that recent raids on large U.S. businesses will hopefully change lawmakers' minds.
During his tenure, Gonzalez was criticized particularly by Democrats and immigration groups for huge backlogs in processing citizens that followed a rush of applications in advance of fee hikes. The backup worsened as many immigrants, who tend to vote more Democratic, sought citizenship in time to vote in this year's presidential election.
Gonzalez said he is proud of his two-year tenure, in which he rolled out a new immigration exam with tougher, more relevant questions, added personnel and expanded training. He even went undercover during his early months to test customer service for himself and found it wasn't client-friendly.
Prior to his work at USCIS, Gonzalez headed western affairs at the National Security Council. Now he is preparing a new kind of agency overhaul, beefing up Indra's U.S. operations.
The company registered about $3.4 billion in revenue last year, but only 3 percent of that was in the United States.
The company and its subsidiaries have provided technology around the globe including voting systems for Venezuela, unmanned drones in Europe and the development, along with Russian scientists, of a prototype laser protection system for large aircraft.
One of the company's subsidiaries, based in the Orlando area, has provided aircraft and weapons simulators for the Department of Defense.
Indra USA is separate. The company will focus on technology for toll roads, financial institutions and municipal governments, including simulators for first responders and law enforcement to help them practice driving their vehicles in urban environments during emergencies.
Gonzalez's immigration experience will also come in handy. Indra happens to provide technology for so-called "smart fences," such as the ones in the works for the U.S.-Mexican border, which combine electronic virtual surveillance with a physical barrier in some cases.


text:
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Herefordshire Through Time
Herefordshire Archaeology
Events, Projects, Publications
Herefordshire's Past
News, events and projects
Gazetteer of Herefordshire castles |
Parishes: A (castles) |
Almeley Castle |
Herefordshire's Past >
The Medieval period >
Gazetteer of Herefordshire castles >
Parishes A >
Almeley Castle
HER no. 1703, OS grid ref: SO 3323 5142
Almeley is a small village in the north-west of Herefordshire, approximately 5 miles from Kington. The motte and bailey earthworks can be found south-west of the village church. The name of the village is derived from the word for "Elm Wood" with the medieval form of Alme-. At the time of the Domesday Survey (1086) it was known as Elmelie, but by the middle of the 11th century it was known as Almeleia. (Bruce Coplestone-Crow, Herefordshire Place-Names, British Archaeological Record British Series 214, 1989, p. 25)
Description of the site today
Beside the church of Almeley is a grass-grown mound, upon which the keep of a medieval castle once stood.
The circular motte is 35m in diameter and 8m in height from the base of the encircling ditch. The ditch is 1.3m deep on the south side and 2.5m deep on the north side below the bailey. The ditch is 8m in width.
The bailey is 50m square and bounded by a ditch on the east side, 12m in width and 2m in depth. The ditch formerly continued around the north side but has since been filled in to form a graveyard extension of the nearby church.
The west side of the bailey is bounded artificial steepening of the natural slopes, presenting a bank 4.5m in height.
Traces of an inner bank can be seen on the north-west side of the bailey, and the original causewayed entrance appears to have been in the east side. To the south-west of the castle motte are two rectangular depressions, which are thought to have been fishponds supplying the castle.
Roughly 50m south-west of the motte, traces of two medieval fishponds can be seen. These fishponds - now dry - are at the foot of a ridge by a stream. One fishpond measures 42m x 20m and the other 50m x 18m. The whole site of the ancient castle is now under pasture.
The motte would have once had commanding views across to the south and east, giving it a defensive advantage.
Foundation and history of the castle
Neither the Domesday Survey nor the earliest lists of border fortifications make any mention of an ancient castle on this site and no evidence exists as to when Almeley Castle was built. It is presumed that the castle was built during the unsettled state of the country during the reign of Stephen, and it appears as a castellum in the Patent Rolls of John and Henry II.
1086: According to the Domesday Book, Almeley had passed into the possession of Roger de Lacy. It included four hides which paid tax, and land for eight ploughs. The men from another village worked in Almeley and paid 37s 8d to do so. It became one of the estates of the de Lacy Honour of Weobley and as such was occupied by Roger Pychard in 1242.
1216: William Cantilupe was constable of the castle in this year.
1231: Henry III received homage from Simon de Montfort when he stopped in Almeley on 22nd September 1231.
In the reign of Henry VII the castle was brought as dowry to Thomas Monnington of Sarnesfield by one of the twelve co-heiresses of Sir Simon Milbourne. Descendants of Thomas Monnington were the owners of Almeley Castle up to 1670.
From the Monningtons the castle passed to the Pembers of Newport and then through purchase to the Foleys of Newport.
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text:
.. _usb_cdc-acm:

USB CDC ACM Sample Application
####################################

Overview
********

This sample app demonstrates use of a USB Communication Device Class (CDC)
Abstract Control Model (ACM) driver provided by the Zephyr project.
Received data from the serial port is echoed back to the same port
provided by this driver.
This sample can be found under :zephyr_file:`samples/subsys/usb/cdc_acm` in the
Zephyr project tree.

Requirements
************

This project requires an USB device driver, which is available for Intel Quark*
SE SoC based boards like :ref:`arduino_101`.  For the Arduino 101 board you need
a USB to 3.3V TTL serial cable.  Connect it to UART1 as described in
:ref:`Connecting Serial Output section <arduino_101>`.

Building and Running
********************

Arduino 101
===========

To see the console output of the app, open a serial port emulator and
attach it to the USB to TTL Serial cable. Build and flash the project:

.. zephyr-app-commands::
   :zephyr-app: samples/subsys/usb/cdc_acm
   :board: arduino_101
   :goals: flash
   :compact:

See :ref:`Flashing the x86 Application Core section <arduino_101>` for details.

Running
=======

Plug the board into a host device, for example, a PC running Linux.
The board will be detected as shown by the Linux dmesg command:

.. code-block:: console

   usb 9-1: new full-speed USB device number 112 using uhci_hcd
   usb 9-1: New USB device found, idVendor=8086, idProduct=f8a1
   usb 9-1: New USB device strings: Mfr=1, Product=2, SerialNumber=3
   usb 9-1: Product: CDC-ACM
   usb 9-1: Manufacturer: Intel
   usb 9-1: SerialNumber: 00.01
   cdc_acm 9-1:1.0: ttyACM1: USB ACM device

The app prints on serial output (UART1), used for the console:

.. code-block:: console

   Wait for DTR

Open a serial port emulator, for example minicom
and attach it to detected CDC ACM device:

.. code-block:: console

   minicom --device /dev/ttyACM1

The app should respond on serial output with:

.. code-block:: console

   DTR set, start test
   Baudrate detected: 115200

And on ttyACM device, provided by zephyr USB device stack:

.. code-block:: console

   Send characters to the UART device
   Characters read:

The characters entered in serial port emulator will be echoed back.

Troubleshooting
===============

If the ModemManager runs on your operating system, it will try
to access the CDC ACM device and maybe you can see several characters
including "AT" on the terminal attached to the CDC ACM device.
You can add or extend the udev rule for your Arduino 101 to inform
ModemManager to skip the CDC ACM device.
For this example, it would look like this:

.. code-block:: none

   ATTRS{idVendor}=="8086" ATTRS{idProduct}=="f8a1", ENV{ID_MM_DEVICE_IGNORE}="1"

You can use
``/lib/udev/rules.d/77-mm-usb-device-blacklist.rules`` as reference.

redpajama_set_name: RedPajamaGithub


text:
2023: Why I won't reveal my favourite candidate - Buhari
President Buhari
President Muhammadu Buhari on Wednesday said he would not reveal his favourite candidate for the 2023 presidency.
Buhari, in an interview, with Channels Television, said he would leave his favourite candidate secret because if he should mention his name, he might be eliminated before the time.
He added that he is not interested who would succeed him and that whoever win would succeed him.
When asked his favourite, Buhari said: "No I will not tell you because he may be eliminated if I mention his name. I better keep it secret."
Hanifa's murder: Buhari wades in, orders police to ensure justice
Buhari passes verdict on El-Rufai: What is it?
Buhari returns to Dodan Barracks, 37 years later
However, the president said he is determined to ensure all killings stopped in the country.
On young Nigerians, the president said his wish was that "when they go to school, work hard, they don't do it thinking government must give them job.
"Education is not just meant to hang on to government to give you job," he said.
Tags: President Muhammadu Buhari


Art enrichment class – how to choose wisely?
Have you noticed that children have too much energy? Children's brains and bodies are developing very fast, and they have a lot of energy which should be released. This process is constant for 15 years and parents should find additional activities that will improve their children's behavior and habits. As you may guess, regular school is not enough. This is the reason why most parents sign their heirs to different sports activities because they hope when kids come at home eventually to be quiet and obedient. Enrichment classes were very popular few years ago and today we may witness to their returning. Most schools have enrichment programs after or before regular classes. Have in mind that they are used more like study hall where kids are nurtured. There are enrichment classes in Singapore where children really learn new things and participate in activities. The difference between sports classes after school and art enrichment classes, like Muzart, is that art class will develop both — mind and body.
Visiting an enrichment class is not something your kid must do but it is recommendable. So the next choice is what kind of enrichment programme to sign for. There are plenty programmes and daycare centers, but we recommend choosing wisely. Forcing your kid to chase a ball half day, if he doesn't want to do that, is not the best option. On the other hand, art classes in Singapore are very popular and improve creativity and discipline. Not long ago there were several studies that prove art classes are stimulating more than creativity and the ability to draw.
What are the advantages of one art enrichment class?
It is not a surprise that art classes are intended for kids of all ages. If you have a toddler at home, there is an art class for him, too. The advantage of participating art class, while growing, is that brain activity is developing faster and some important character traits are formed easier. For example, children who are signed for enrichment class learn not only how to draw but how to hold a pen, how to make difference between colors, how to choose what to paint on the white paper and what means one drawing comparing to another. Children in art classes in Singapore are better problem solvers. If you have some doubt, try to imagine how many possible ways there are to draw one house. When children faced the opportunity to choose what to draw and how exactly to do it, they become better thinkers and problem solvers really fast.
In addition, art classes as part of enrichment programme are developing creativity and valuable ability to express your mind and feelings. One of the first things that children learn in the class is a different influence on the color. Why one color is considered warm, another — cold. In higher levels of the class, they try to explain and to analyze paintings of famous artists, because art has a lot in common with analyzing and understanding.
Children develop their creativity due to a lot of fun games and activities.
Different levels of the art class include finger painting, collage making and etc. if you are afraid, that art classes in Singapore are not fun enough, you should check how many funny ways there are to paint and draw. Teachers are paying an extra attention to all kids and you will notice it when your child starts to bring at home his works. Some children draw things that adults can't draw thanks to good teachers and educational methods. Art enrichment class is a wise choice when you are looking for a class that will develop your child's mind and body.
Why should you choose phonics class for your kid?