Data Driven Applications for the Internet of Things
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Data Driven Applications for the Internet of Things

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This case study outlines the role Red Ninja Studios played in the user-led design and development of data driven web applications that explore the Internet of Things, the challenges of Big Data......

This case study outlines the role Red Ninja Studios played in the user-led design and development of data driven web applications that explore the Internet of Things, the challenges of Big Data and how Hypercat streamlines the development process and mash-up of data to create value.

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  • 1. Internet of things TSB project CASE STUDY: DATA DRIVEN APPLICATIONS V1.20 Xi Sizhe, Lead Developer Steven Hassall, Senior Designer Lee Omar, CEO 5.3
  • 2. Red Ninja Studios This case study outlines the role Red Ninja Studios played in the user-led design and development of data driven web applications that explore the Internet of Things, the challenges of Big Data and how Hypercat streamlines the development process and mash-up of data to create value. 2
  • 3. THE CHALLENGE OF INTEROPERABILITY IN THE INTERNET OF THINGS • Lack of context awareness: Sensor data is not helpful and we need to integrate with other objects and make the sensor data become knowledge that can be re- used and shared (aware of location, time, event) • Each vendor has it’s own API, with different syntax; Decoupling Publishers and consumers – inconsistent Semantic / Ontology means not data driven • App developers are data consumers and knowledge base builders, who receive many datasets that are combined to create value. The datasets are typically beyond the control of app developers, so moving forward and by collaborating with data publishers such as AlertMe, EnLight, Intellisense.io and Hypercat (1248.io), we can establish semantic data and quickly explore contextual data that is pragmatic and in line with IOT and open web thinking 3
  • 4. Hypercat: Linking Data • Hypercat will help future developments as app’s must be context aware and semantic metadata exposes information at the application level that is understandable at the machine level • Hypercat encourages the standardisation of open data and API’s when accessing third party data, promoting intuitive and intelligent app development, across devices and in keeping with the spirit of the internet of things • Hypercat provides interoperability of data between data publisher and data consumer and separates the responsibility between them (one for tagging and one for linking) 4
  • 5. EXTRACTING VALUE FROM BIG DATA VIA CO-CREATION 5 Problem Available Resources Solution AlertMe smart sensor installed in Willow room at ARM, Cambridge ? We participated in focus groups and interviewed employees across the various departments at ARM’s Cambridge campus to try and get a real understanding of day to day working life and ensure a user led design approach to our process. From the co-creation process, we identified the following common problems experienced by employees; meeting room availability, heating comfort issues and raising awareness of energy efficiency. Our solution would utilise Hypercat to access internet of things (IOT) assets published via AlertMe, EnLight and Intellisense.io and ARM. Assets include; motion, light, temperature, parking sensors and HVAC systems and room data.
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  • 8. Meeting Room App • PROBLEM: A person books a room from 3pm to 5pm, leaves the room at 4pm and then the room is left empty for an hour. With a high demand for meeting space, employee’s are often left frustrated • SOLUTION: Use the live motion sensor data to see instantly which rooms are available • Simple Logic: Pink means unavailable and blue means available • Compliments not replaces the existing Outlook room booking system and empowers users with a more responsive experience when searching for room availability • By crawling motion sensor and location data via Hypercat catalogs and linking them together, we created a knowledge base that allows easy development and mashing-up of data for the meeting room application • Clicking hexagon reveals more booking room information and clicking ‘I’ then reveals that days itinerary. This is live data pulled in from the Outlook booking system 8
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  • 11. Heat Map App • Another common problem ARM employees talked about was their office being too cold • To help management and maintenance monitor this, we have a live heat map that visualises temperature consistency or inconsistency (as it might be), across the office space • This will also highlight potential cold spots and insulation weaknesses • External car park sensors are also positioned dynamically via geo-location 11
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  • 13. AlertMe Home Energy App • Challenge: Increase engagement of Homes using the AlertMe energy monitoring kits • Solution: With a sprinkle of gamification, we ranked energy usage and in turn the money saved by each home, revealing to participants how their home is performing compared to their neighbours • Peer pressure can be a strong motivator • Money talks and can inspire users who may not realise potential savings 13
  • 14. 14 This is how we built the process pipeline to consume and reuse the catalogs for different applications. Data Crawl starts the process, we request data via Hypercat
  • 15. 15 We then store this data in local repositories and the important part here, is in the mapping block, where the various sensor data is linked or mapped together
  • 16. 16 We now have all this semantic data stored locally in knowledge bases, we need to query this to extract value within our application
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  • 19. IOT LESSONS LEARNT • Future applications not only need to be cross platform or real time but to be smart and data driven. Ensuring applications are context aware in terms of location, event, people, sensor data • By exposing meaningful resources from standardised catalogs such as those via Hypercat, different sources of data are easily integrated, allowing us to build a knowledge base for the uniform understanding of data • Taking this data and applying web semantics, allows contextual and data driven apps that speed up the development process • Hypercat allows us to maintain such data sources consistent with data vendors 19
  • 20. HYPERCATS LONG TERM VALUE; STREAMLINING THE DEVELOPMENT PROCESS • We often work with multiple data publishers, so a lot of our time is spent understanding proprietary API’s and web data formats • The project itself has provided Red Ninja with a streamlined development environment, with us being able to easily mash-up multiple data streams published by ARM, Intellisense, AlertMe, Enlight, via Hypercat and focus on the design and development of the app’s, less on issues of compatibility • For us Hypercat is a forward thinking and open web initiative that has the potential to benefit many developers across the world 20
  • 21. Copyright 2014 Red Ninja Ltd 21 Follow us: @RedNinjaStudios Contact: info@redninja.co.uk