Cost of reliable Air Quality Monitors (AQM) and the scalability of communication infrastructure have made real time monitoring of air pollution at high geospatial density unattainable until now. We aim to make this a reality by solving some of the underlying scientific and technological challenges. We have developed a novel low-cost AQM node that utilizes cost-effective electrochemical sensors to measure Carbon Monoxide (CO) and Nitrogen Dioxide (NO2) concentrations and an infrared sensor to measure Particulate Matter (PM) levels. The node can be powered by either solar-recharged battery or mains supply. It is capable of long-range and low power communication over public or private LoRaWAN IoT network and short-range high data rate communication over Wi-Fi. Our design won the Keysight IoT Innovation Challenge in the Smart Land category by beating regional competitors from universities like Nanyang Technological University, Australian National University, University of Auckland etc. and the Massachusetts Institute of Technology (MIT) in the global competition. Our current focus is to utilize the “Big Data” acquired through the AQMs to develop machine learning based novel calibration and forecasting algorithms.

Our work on low cost IoT enabled remote sensors was instrumental in monitoring the seawall at Auckland harbour. The wall under the historic Ferry Building was damaged and it was vital to monitor the wall in real time. Due to the urgent nature of the repairs, a solution was required to be ready for deployment within 2 weeks. We developed a remote monitoring system that was deployed before the deadline and was used during Nov’17- April’18.

We have partnered with Scion to develop a remote sensor network for end-to-end supply chain monitoring. The prototype was recently trailed by the scientists of Scion.