These applications provided visualisations of mobile device positions on interactive maps of both indoor facilities and aerial/satellite imagery. They combined signals acquired from disparate things including Bluetooth low energy beacons, Internet routers, and GPS signals. To speed development, the students made extensive use of open source software including iOS and Android mobile location apps, as well as sigma.js and node.js to support the browser-based functions.
One application allowed users to search for other registered users on their mobile devices and view a heat map that displayed realtime people traffic and historical data. The other app provided visualization of the IoT network nodes and data including the applications, users, devices, and the aggregated IoT sensor data. Users could directly edit the graphical representation of the network, using a cursor to select specific nodes on their display for editing, as well as creating new nodes, or searching for nodes not displayed. In this way, users could easily add, update or delete data.
These applications were written by students and required 600 and 1,000 person-hours of work each. They are representative of future IoT applications that will easily combine data from multiple and disparate sources, providing insights that enable smart decisions. The underlying technology solutions that can perform the required data aggregation, sensor service management, and application integration are maturing quickly.
Jim Ballingall is executive director of The Industry-Academia Partnership, an association of university professors, students and industry leaders in pursuit of common goals in cloud computing education, research and product development.