The BC Ministry of Transportation and Infrastructure (MOTI) is seeking a proof-of-concept solution to demonstrate innovative applications of analytics on camera and sensor data consolidated on their Proof of Concept (POC) IoT platform so that they can prove the technology concepts and learn from a properly defined technology model.
MOTI wants to increase its understanding of the trends in its data so that it can do long-term planning, such as make the case to build or repair infrastructure like roads and bridges, and look for ways to enhance decision-making processes with the ministry. Build a POC data analytics extension to our MOTI open source IoT platform that analyzes sensor and camera data and provides information for decision-making by MOTI business users with data flowing from MOTI’s Proof of Concept IoT platform. The POC could support data query and visualization across sensor types and granularity and include geospatial, historical and real-time data. This challenge is an opportunity for tech firms to discover MOTI’s needs and demonstrate innovations that MOTI should be considering when developing multiple new capabilities to analyze IoT data for different users.
Visualization, querying and analysis of large-scale, real-time systems are intrinsically challenging data management tasks. To extend the value of taxpayer investment in the vast and growing stores of accumulated sensor and camera data within the Ministry, MOTI is seeking to demonstrate innovative uses from this data through IoT-enabled analytics for our dynamic transportation system. The initial focus of the challenge will be on creating actionable information for MOTI business units. Examples include:
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Provide an interactive, web-based, geospatial interface to extract, consume and analyze data from a variety of sensors.
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Facilitate the creation and use of customized geospatial queries across large-scale sensor data sets.
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Combine information from different internal and external sources to provide added value.
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Enable real-time and historical visualization, querying and analysis of sensor data.
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Support data visualization across sensor types and granularity of data to improve the understanding of correlations in the data across sensors. For example, overlaying data from different sensors at the same time and granularity to see the impact of an event in one sensor on others.
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Automatically detect correlations in streams of data from multiple sensors. For example, an event in one sensor predictably follows a pattern of events in other sensors.
A key goal of the IoT analytics platform is enabling MOTI to build its own visualizations to improve both tactical decision making at the operations level and strategic decision-making at the Executive level. On the former, MOTI wants to enable real-time situational awareness in the handling of events – proactive delivery of the needed data to those handling a situation. On the latter, it’s about giving Executives useful direct access to drill into and explore the data to better understand the forces and trends affecting the business in the long term.
We want to ensure that we leverage current data services and infrastructure, minimizing data duplication and maximizing re-utilization, and implement data transformation and conversion mechanisms.
Data analytics could include year-over-year data comparison, patterns, high/low/average values, volumes, spatial analysis, and more relating to speed, congestion, weather and seismic.
For example:
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Changes in traffic patterns in response to events
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Analytics and performance indicators to show maintenance activities
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The number of times trucks need to distribute salt on a stretch of road
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Locations where people tend to slip off the road, highlighting problem areas
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.