Smart city projects collect dynamic data with a view to supporting service delivery, providing timely information to domain experts such as local government and planning departments, and to guide longer-term decision making. As such, the Manchester based CityVerve project is making available numerous, diverse streams of live, real-time Internet of Things (IoT) data such as healthcare, air quality and transport, published as ‘open data’ via publicly available application programming interfaces (APIs).
To make this data available to as many users as possible, it is important that the APIs are accessible and easy to use to enable them to explore the data and find what they require. To address this challenge, Ann has led the design of a ‘CityVerve data dashboard’ to support these users to obtain an understanding of key features of individual streams, and to undertake a variety of analyses that inter-relate multiple city data sources.
The data dashboard combines technologies such as Django, JSON, InfluxDB and Python Pandas to allow those interested in sensor data to easily browse, view, manipulate and analyse the published streams; for example to observe current carpark or building energy consumption figures alongside weather data, or bicycle and car journey data at different times of the day.
It is envisaged that there is a diverse set of potential users of smart city data, each viewing the data through the prism of their own experiences and perspective. Enabling such a diverse user-set to explore multimodal cross-thematic data in turn increases the potential to find useful patterns to meet a city's needs.
The paper ‘A smart city dashboard for combining and analysing multi-source data streams'; Ann Gledson, Thamer Ba Dhafari, Norman W Paton and John A Keane; was presented at SmartCity-2018, 28-30th June 2018, Exeter, UK.
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