Light Pollution Monitoring Using A Modular IoT Sensor Platform


Light pollution, caused by indiscriminate use of artificial lighting at night, is a growing threat to astronomy, the environment, and other fields. Monitoring light pollution can help inform local communities on its impact on their environment, especially nocturnal plants and animals, such as sea turtles. However, existing systems for light pollution monitoring are expensive, non-scalable, and uni-directional, while others are inaccurate and cannot be deployed at a large scale. In this paper, we propose a modular IoT sensor platform called Pasteables with reconfigurable and easily replaceable components. We tailor this sensor platform to use many of the sensors related to monitoring light pollution. It builds upon our previous work that shares the idea of a generic modular sensing platform. Unlike the previous work, we created new designs for the Components for Uniform Interface (CUI) with sensors, including light sensor, temperature/pressure sensor, and GPS. We fabricated PCB proto-types of this Pasteables platform using FR-4 material and surface mount components. Each CUI connects to the base pad using edge connectors to make the CUIs reconfigurable during installation. With these prototypes, we evaluated its responsiveness and sensitivity at two different locations of varying heights for the light source against the least expensive existing solution.

2022 IEEE International Conference on Smart Internet of Things (SmartIoT)
Reiner Dizon-Paradis
Reiner Dizon-Paradis
Postdoctoral Research Associate

My research interests include machine learning applications in national security, hardware security and assurance, artificial intelligence of Things, and robotics.