1. Technical Field
The invention is related to RF-based location tracking systems, and more particularly to a process employed in such systems for determining the location of persons and objects carrying radio frequency (RF) transmitters that transmit data messages to a plurality of RF receivers connected to a computer in a computer network. The receivers forward data received from the transmitters to the network, along with radio signal strength indicator (RSSI) data, for computation of the location of the person or object carrying each transmitter.
2. Background Art
Knowledge of the indoor location of people and objects is widely considered to be a key enabler to the viability of many current mobile and ubiquitous computing schemes. These applications include location-sensitive messaging, location-based reminders, and activity inferencing, among others. For example, in a mobile computing environment, a user of a mobile computing device (e.g., notebook computer, handheld PC, palm-size PC, Personal Digital Assistant (PDA) or mobile phone) may wish the device to provide directions to a particular location in a building, such as the nearest printer, snack room, restroom, etc., or perhaps directions to a particular conference room or office within the building. This type of information is dependent on knowing the current location of the user. Mobile computing device users also typically expect messages and other notification information to be provided to them wherever they happen to be. However, some notifications can be dependent upon the user's location. For instance, a user might be notified that he or she is near a printer where a user-submitted document has been printed. Again the user's current location is needed to make such a notification. A mobile computing device user might also want to know the location of other people in the building, in order to find them or obtain information about them. For example, a user might want to get a list of the names of people attending the same meeting. To obtain this information, it is necessary to know what people are at the location of the meeting. The foregoing are just a few examples of the need to know the location of people. It is easy to imagine many other situations where knowledge of the location of people would be useful.
Location information is equally critical in so-called ubiquitous computing. Ubiquitous computing revolves around extending computational activities beyond the current desktop model and into the environment. In future homes and offices, access to computing should be as natural as access to lighting. Users should not be required to go to a special place (i.e., the desktop) to interact with the computer. Rather, the computer should be available to interface with the user anywhere in the home or office (or more generally anywhere in an arbitrarily large environment), through whatever set of devices is available, be they fixed or carried by the user.
It is noted that the term computer is used loosely here in that the user actually would have access to a wide variety of computing and information services, which will likely employ many computers and “smart” devices such as the aforementioned PDA's, mobile phones, etc. For example, computing services such as web browsing, document editing, or video conferencing are envisioned. Thus, it should be understood that when the term computer is used in connection with the concept of ubiquitous computing, in actuality many computers may be involved non-exclusively in a single interactive session.
The usefulness of a ubiquitous computing system hinges on the ability to maintain an awareness of the users, particularly their locations. One goal of such a system would then be to understand the physical and functional relationship between the users and various I/O devices. This knowledge could be employed to allow a user to move from room to room while still maintaining an interactive session with the computer. In addition, knowledge about whom and what is in the vicinity of a person can be used to tailor a person's environment or computing session to behave in a context-sensitive manner. For example, knowing the location of a person in a building can be used to infer what activity that person is engaged in and then the environment or computing session can be adjusted appropriately.
While the location of static things such as furniture, big displays, and desktop computers can reasonably be measured manually, the locations of things that move, including people, demand automatic measurement. The Global Positioning System works well outdoors, but there is not yet a comparably ubiquitous and inexpensive technology for measuring location indoors. Even so, there are several current technologies for automatically determining the location of people and objects in indoor spaces. For example, one of the first of such location systems uses diffuse infrared technology to determine the location of people and objects in an indoor environment. A small infrared emitting badge (sometimes referred to as a button or tag) is worn by each person, or attached to each object, whose location is to be tracked. The badge automatically emits an infrared signal containing a unique identifier every 10 seconds, or upon request of a central server. These requests are transmitted to the badges via a series of fixed infrared sensors placed throughout the indoor environment—typically mounted to the ceiling. The sensors also receive the infrared emissions from badges within their line-of-sight. The central server, which is hardwired to each sensor, collects the data received by the sensors from the badges and provides it to a location program for processing. These types of systems do not provide the actual 3D location of the person or object carrying the badge. Rather, the person's or object's location is deemed to be within the room or area containing the infrared sensor that received the emission from the badge attached to the person or object. In addition, these systems, being infrared-based, are susceptible to interference from spurious infrared emissions from such sources as fluorescent lighting or direct sunlight. Further, diffuse infrared-based systems have a limited range, typically only several meters. Thus, except in small rooms, multiple sensors are required to cover the area. In addition, since the sensors must be within the line-of-sight of the badges, a sensor must be placed in every space within a room that cannot be seen from other parts of the room. As a result, a considerable number of sensors have to be installed and hardwired to the central server. This infrastructure can be quite expensive and in some cases cost prohibitive.
Other existing indoor location systems attempt to improve the accuracy of the location process using a combination of radio frequency and ultrasonic emission. In these systems, a central controller sends a request for location data via a short range radio transmission to each badge worn by the people, or attached to the objects, whose location is being tracked. In response, the badges emit an ultrasonic pulse to a grid of fixed receivers, which are typically mounted to the ceiling. Each receiver that “hears” the ultrasonic pulse emitted from a badge reports its distance from the badge to the central controller via hardwired connections. Specifically, a synchronized reset signal is sent to each receiver at the same time the location request is transmitted to the badges. This reset signal starts a timing procedure that measures the time between the reset signal and the receipt of an ultrasonic pulse for a badge within range of the receiver. The receiver then computes its distance from the badge emitting the pulse and reports this to the central controller. An ultrasound time-of-flight lateration technique is then used by the controller to accurately determine the locations of the badges. While these types of systems do provide very accurate location information, they again require an expensive infrastructure in form of multiple receivers mounted throughout the environment which must be hardwired to the central controller. In addition, the accuracy of these systems has been found to be adversely affected if the placement of the receivers is less than optimal. Further, there is a concern associated with animals being sensitive to ultrasonic emissions.
A variation of the combined radio frequency and ultrasonic location system requires the badges to determine their own location, presumably to compute directions, and the like, and to provide the information to a person carrying the badge. In this case there is no centralized controller that determines locations of all the badges. Specifically, ultrasonic emitters are mounted in various locations around an indoor space. The badges include a radio frequency transceiver. Whenever location information is desired, the badge transmits a radio frequency signal. The emitters pick up the signal from the badges and respond with an ultrasonic pulse. The badge unit measures the time it takes to receive each ultrasonic pulse emitted by an emitter within range of the badge. In addition to the ultrasonic pulse, the emitters also transmit a radio frequency signal that identifies the emitter and its location. From the timing and emitter location information, the badge triangulates its own position. The infrastructure is not as problematic in this latter system since there can be fewer emitters and they are not hardwired into any kind of centralized controller. However, only the badge unit knows its location. Thus, there is no centralized database to provide location information to help locate persons in the building. In addition, the badges are relatively complex in that they must include both a radio frequency transceiver and an ultrasonic receiver, as well as the processing capability (and so power burden) to compute their location.
In yet another indoor location system [2], radio frequency LAN wireless networking technology is used to determine the position of people, or more specifically a computing device employing the wireless LAN technology (such as a notebook computer). In this system, base stations are deployed within the indoor environment to measure the signal strength and signal to noise ratio of signals transmitted by the wireless LAN devices (or vice versa where the mobile computer receive signals transmitted by the fixed-location base stations and measure the signal strength and signal to noise ratio thereof). A centralized program takes the signal information and employs a lateration process to estimate the location of the transmitting unit. More particularly, the location estimation process involves using signal strength in a nearest neighbor analysis among the base stations, and employs a rudimentary Viterbi-like algorithm [4] to help smooth trajectories. This system has the advantages of requiring only a few base stations and using the same infrastructure that provides the building's general purpose wireless networking. However, the person or object being tracked must have a device capable of supporting a wireless LAN, which may be impractical on small or power constrained devices.
The Nibble [5] system also uses wireless LAN signals to compute locations in a building. It uses the measured signal-to-noise ratio instead of absolute signal strength. Nibble is based on a Bayesian network to compute the probability of being at any of a set of discrete locations in the building. Nibble's Bayesian network also supports the inclusion of transition probabilities between nodes.
Other current systems also employ radio frequency technology to locate people and objects in an indoor environment. One such system uses a centralized base station and a series of antennas spread throughout the environment that each emit a RF request signal which is received by badges within range of the antenna. These badges, which are attached to people and objects whose location is being tracked, transmit a RF signal in reply with an identifying code embedded therein. The location of the badge relative each antenna is computed using a measurement of the time it takes for the base station to receive the reply via the various antennas after the request is transmitted. However, the antennas have a narrow cone of influence, which can make ubiquitous deployment prohibitively expensive.
In another RF based system, users approaching a PC are automatically logged on by virtue of their wearing a badge transmitting RF. The receiver connects to the PC via RS-232. Although this system was not designed to measure location in a building, Hightower et al.[1] investigated its use for location measuring in a room. They measured 3D location based on multiple receivers and an empirically derived function giving signal strength as a function of distance to the receiver. The hardware limited signal strength measurements to two bits, which in turn limited the system's resolution to a cube of three meters on a side. In addition, it took 10 to 20 seconds to gather readings from all the receivers into the central database for the computation of a single 3D location.
Electromagnetic sensing is also employed for position tracking. These types of systems generate axial DC magnetic field pulses from a fixed antenna. The system then computes the position of the receiving antennas by measuring the response in three orthogonal axes to the transmitted field pulse. However, the infrastructure needed for these systems is expensive and the tracked object must be tethered to a control unit.
Finally, position tracking has been accomplished using computer vision techniques. In these systems, cameras are employed to determine where persons or objects of interest are located in an indoor environment. While these types of position tracking systems can be quite accurate, the processing required to analyze each camera frame is substantial, especially when complex scenes are involved. Thus, the infrastructure costs for these systems can be very high.
It is noted that in the preceding paragraphs, as well as in the remainder of this specification, the description refers to various individual publications identified by a numeric designator contained within a pair of brackets. For example, such a reference may be identified by reciting, “reference [1]” or simply “[1]”. Multiple references will be identified by a pair of brackets containing more than one designator, for example, [2, 3]. A listing of references including the publications corresponding to each designator can be found at the end of the Detailed Description section.