• Project Objectives
• Context Diagram
• Conceptual Architecture
• Application of Architecture to Use Case
• Use Case Questionnaire Extract
• Derive the state of a
fleet of freight vehicles
• Provide more timely
• Reduce risk
• Reduce vehicle
• Decrease costs
Schedule Event mm endat
Capture Process Respond
Applications Configuration Management
– Acquire events from various disparate sources
including trucks and enterprise systems
– Apply rules to events to build state of fleet and
identify ‘derived events’
– Transmit derived events to interested users and
How does this translate into a use case?
• Maintaining a model of the state of a fleet of freight vehicles
• Derived from disparate sources such as EDI, asset management systems,
on board sensors…
• Notifications to drivers, maintenance depots, asset management
• Initial objective is to provide more timely maintenance and so reduce risks
• Long term leverage the infrastructure to derive more value from the
various flows of events, e.g. common component failures
Inputs, Outputs and Users
Sources Web services, MOM, real-time GPS and sensors via onboard
Vehicle Management System over mobile IP, RDBMS (for
data not exposed via web services)
Input: types of data Vehicle reference data, driver info., maintenance
schedules, maintenance depot locations, depot availability,
intended destination, route, location, vehicle health
Central Aasset management system, SMS, Email,
Output: types of data Alerts of imminent failures, less urgent maintenance
requests, dashboards showing fleet health and current
alerts, etc., map based views of geospatial data
Channels From Web Service, MOM and File adapters to State Engine,
Dashboards and SMS Adapter all internal transport
Users Fleet experts add rules, drivers respond to alert SMS,
system operators (monitor health of solution itself), fleet
managers monitor health of system and maintenance cost
Filter Irrelevant data from the engine management system
Enrichment Some data types enriched with geospatial data
Transform Various EDI and XML forms into a standard internal format
and various to go from standard to file, SMS and web
Aggregation Both current and historical health aggregated across fleet
by various measures
Specific sequences Identified issues (e.g. need for maintenance) must be
actioned in time. Correct sequence and timeliness of such
action events is monitored.
Trends over sequences Identify trends in truck telemetry as indicators of possible
truck health issues.
Query the state stored in a Current alerts and other current state that drive
Rules over a state Reported traffic problems (event or state) correlated with
latest position of truck (event or state) and its intended
route (state) to suggest re-routing.
Problem detected by Vehicle Management System (event)
indicates maintenance needed – compare with intended
route (state) and maintenance depots (state) to identify
where to fix it.
Describe reactions SMS and email for urgent maintenance problems, email
and web service notification for less urgent.
Dashboards to show current alerts and overdue alerts and
overall fleet health.
Email for overdue alerts.
Scale Hundreds to tens of thousands of vehicles.
Latency Latency is not a particular issue so of the order of seconds
rather than milliseconds is acceptable (guaranteed
processing is more important).
Patterns For every vehicle there may be tens of patterns being
detected so this equates to tens to hundreds of thousands
across all vehicles. Some patterns may be ‘live’ for months
(more akin to state).
Variable Load EDI transactions may tend to arrive in large batches.
Systems Management System should notify operators of its own health and
identify performance hotspots.
Event Center and Greentrac Products
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