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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 and how Hypercat streamlines the development process and mash-up of data to create value.
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Internet of things TSB project
CASE STUDY: DATA DRIVEN APPLICATIONS
V1.20
Xi Sizhe, Lead DeveloperSteven Hassall, Senior DesignerLee Omar, CEO
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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.
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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
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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)
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EXTRACTING VALUE FROM BIG DATA VIA CO-CREATION
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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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
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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
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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
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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
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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
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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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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
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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