SIParCS 2024 - Abrar Hossain
Abrar Hossain, University of Toledo
Environmental Data Sensing and Monitoring System Using Community-based Private LoRa Network
This project aims to establish a mesonet of IoT weather monitoring sensors to gather comprehensive environmental data, including temperature, humidity, altitude, air quality, UV levels, and rainfall. Building on existing techniques for LoRa (Long Range), we design an experiment to set up a community-maintained private LoRa network, the sensors will transmit data to intermediary custom Raspberry Pi gateways, which will then forward the aggregated data via the internet to a network server. This server will distribute the information to various application servers for further processing and analysis. Key components include sensor devices equipped with LoRa communication capabilities, Raspberry Pi gateways acting as local data aggregators, a central network server, application servers for data processing, and a join server for secure communication. The collected data can be made AI ready and used for weather modeling to improve local weather predictions, real-time alert systems for severe weather conditions, continuous environmental monitoring to assess pollution and climate change impacts, agricultural applications to optimize irrigation and protect crops, and urban planning to design resilient infrastructure. This project further aims to enhance local weather prediction accuracy, improve community preparedness for severe weather, and leverage the power of edge computing, particularly by implementing edge-ML technologies within LoRa environmental data sensing contexts for edge inference on IoT hardware.
Mentors: Keith Maull, Agbeli Ameko
Slides and poster