The BC Ministry of Transportation and Infrastructure (MOTI) is looking to demonstrate dynamic event stream processing to evaluate and respond to camera and sensor data via our prototype IoT platform so that we can prove the technology concepts and learn from a properly defined solution.
MOTI wants to enhance the way it evaluates the data coming from its devices, so that it can take actions like changing traffic flows, respond to road events, or send out a maintenance crew. Build a Proof of Concept (POC) to demonstrate dynamic event stream processing of sensor and camera data via MOTI’s prototype IoT platform. The POC should parse camera and sensor messages and events in real time through configurable set of rules defined by business users that allows for automated decision making.
We want business-user-defined rules to define event-driven results based on real-time data, the current state of local and grouped devices, historical, aggregated and summarized data, and external data sources.
This challenge is an opportunity for tech firms to discover MOTI’s needs and demonstrate innovations that MOTI should be considering when developing new capabilities to process, manage and understand IoT data.
Our goal is to have data-driven events governed by business-user-configurable rules integrated with our open-source IoT platform.
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We want to see real-time, automated data responses that enable people to make decisions using visual indicators, event notifications and escalations by role, location, and real-time public alerts and notifications.
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For efficiency and safety, the solution should provide automated decision-making processes through Intelligent Traffic Management systems; and, demonstrate automated mitigation (e.g., through actuators, signs, etc.) causing event-based device actions.
The solution will also demonstrate a user interface to allow business users to define customized rules and responses for event processing logic. It should provide business-user customizable and extendable business-user-defined logic, configurable rule-sets, be extendable to new sensor types, sensors and data sources, and offer ease of configuration through the user interface.
As part of this challenge, we would involve our challenge partners to assist with designing and standing up our APIs in support of our modular, open-platform approach.
Example scenarios include:
- Sensor Thresholds: Perform an action when a sensor threshold is reached within a given period.
- Data Validation: Perform an action when there is a temperature that exceeds expected norms.
- Sensor Configuration: Modify sensor parameters when a threshold or range is met.