Actors/Stakeholders and End-users (Sender/Recipients) their roles and Transport Handlers (Truck/Ship/Plane) responsibilities Telecom Providers (Cellular/SATCOM) Shippers (Shipping and Receiving) Goals Retention and analysis of items (Things) in transport Use Case Description The following use case defines the overview of a Big Data application related to the shipping industry (i.e. FedEx, UPS, DHL, etc.). The shipping industry represents possible the largest potential use case of Big Data that is in common use today. It relates to the identification, transport, and handling of item (Things) in the supply chain. The identification of an item begins with the sender to the recipients and for all those in between with a need to know the location and time of arrive of the items while in transport. A new aspect will be status condition of the items which will include sensor information, GPS coordinates, and a unique identification schema based upon a new ISO 29161 standards under development within ISO JTC1 SC31 WG2. The data is in near real-time being updated when a truck arrives at a depot or upon delivery of the item to the recipient. Intermediate conditions are not currently known, the location is not updated in real-time, items lost in a warehouse or while in shipment represent a problem potentially for homeland security. The records are retained in an archive and can be accessed for xx days. Current Compute(System) Unknown Solutions Storage Unknown Networking LAN/T1/Internet Web Pages Software Unknown Big Data Data Source Centralized today Characteristics (distributed/centralized) Volume (size) Large Velocity The system is not currently real-time. (e.g. real time) Variety Updated when the driver arrives at the depot (multiple datasets, and download the time and date the items were mashup) picked up. This is currently not real-time. Variability (rate of Today the information is updated only when the change) items that were checked with a bar code scanner are sent to the central server. The location is not currently displayed in real-time. Big Data Science Veracity (Robustness (collection, Issues) curation, Visualization NONE analysis, Data Quality YES action) Data Types Not Available Data Analytics YES Big Data Specific Provide more rapid assessment of the identity, location, and conditions Challenges (Gaps) of the shipments, provide detailed analytics and location of problems in the system in real-time. Big Data Specific Challenges in Mobility
Actors/Stakeholders and their roles and responsibilities End-users (Sender/Recipients) Transport Handlers (Truck/Ship/Plane) Telecom Providers (Cellular/SATCOM) Shippers (Shipping and Receiving) Goals Retention and analysis of items (Things) in transport Use Case Description The following use case defines the overview of a Big Data application related to the shipping industry (i.e. FedEx, UPS, DHL, etc.). The shipping industry represents possible the largest potential use case of Big Data that is in common use today. It relates to the identification, transport, and handling of item (Things) in the supply chain. The identification of an item begins with the sender to the recipients and for all those in between with a need to know the location and time of arrive of the items while in transport. A new aspect will be status condition of the items which will include sensor information, GPS coordinates, and a unique identification schema based upon a new ISO 29161 standards under development within ISO JTC1 SC31 WG2. The data is in near real-time being updated when a truck arrives at a depot or upon delivery of the item to the recipient. Intermediate conditions are not currently known, the location is not updated in real-time, items lost in a warehouse or while in shipment represent a problem potentially for homeland security. The records are retained in an archive and can be accessed for xx days. Current Solutions Compute(System) Unknown Storage Unknown Networking LAN/T1/Internet Web Pages Software Unknown Big Data Characteristics Data Source (distributed/centralized) Centralized today Volume (size) Large Velocity (e.g. real time) The system is not currently real-time. Variety (multiple datasets, mashup) Updated when the driver arrives at the depot and download the time and date the items were picked up. This is currently not real-time. Variability (rate of change) Today the information is updated only when the items that were checked with a bar code scanner are sent to the central server. The location is not currently displayed in real-time. Big Data Science (collection, curation, analysis, action) Veracity (Robustness Issues) Visualization NONE Data Quality YES Data Types Not Available Data Analytics YES Big Data Specific Challenges (Gaps) Provide more rapid assessment of the identity, location, and conditions of the shipments, provide detailed analytics and location of problems in the system in real-time. Big Data Specific Challenges in Mobility