Better Smart Campus Sensor Technologies
Smart technologies enable more efficient use of built environments. Spaces can be better used, personnel better deployed, and energy consumption/emissions reduced while maintaining a pleasant environment. Sensors measure parameters like temperature, air quality, movement, or sound. Data from sensors is analysed using machine learning techniques. Open information enables diverse stakeholders to make informed decisions, e.g. students can locate a quiet and available study area, building management can adjust climate control, supervisors can determine staffing requirements.
The University of Glasgow (UoG) plans to build such intelligence into the new campus. As a testbed the UoG project team have developed and are evaluating a deployment of Raspberry Pi supersensors. The Radboud University (RU) have designed complementary software technologies in the form of the Clean/iTasks/mTask framework that can control such a network with a single program.
Our project aims to explore better software and hardware integration for the UoG Smart Campus. The technical aim is to develop and evaluate a usable IoT solution that is durable, safe, secure, maintainable and minimises costs and emissions. We will explore the ability of the radical new Clean/iTasks/mTask technologies from Radbound University (RU) to achieve these goals when deployed on both existing UoG CS Supersensors and on cheaper microprocessors like the Espressif ESP8266.
The target outcome is to improve the UoG smart campus network technology to employ cheaper sensors in a network that has lower power consumption & emissions, while being easier to construct and adapt to the changing needs of various stakeholders.
a) To establish a long-term research collaboration in developing better Internet of Things software technologies.
b) To conduct a focused study into appropriate hardware and software technologies for the UoG smart campus. The goals for the sensor hardware are to be durable, maintainable and to minimise cost, and to achieve this we will use commodity devices. The goal for the software is that it should be safe, secure, maintainable and fast to develop. We will explore the ability of the Clean iTask and mTask technologies from Radboud CS to achieve these goals when deployed on both the UoG CS Supersensors and on small and cheap sensors like Espressif ESP8266.
c) To produce a paper for a premier venue like IEEE Pervasive Computing, IoT World, WF-IoT, IoTAIS, IoTDI that describes our results, and a body of open-source software. In the longer term the project will cement a collaboration between two world-leading research groups, leading to joint projects, papers, open source software, and education activities.