Department Publications

We introduce a novel LoRa-based multi-hop communication architecture as an alternative to the public internet for earthquake early warning (EEW). We examine its effectiveness in generating a meaningful warning window for the New Zealand-based decentralised EEW sensor network implemented by the CRISiSLab operating with the adapted Propagation of Local Undamped Motion (PLUM)-based earthquake detection and node-level data processing. LoRa, popular for low-power, long-range applications, has the disadvantage of long transmission time for time-critical tasks like EEW. Our network overcomes this limitation by broadcasting EEWs via multiple short hops with a low spreading factor (SF). The network includes end nodes that generate warnings and relay nodes that broadcast them. Benchmarking with simulations against CRISiSLab’s EEW system performance with internet connectivity shows that an SF of 8 can disseminate warnings across all the sensors in a 30 km urban area within 2.4 s. This approach is also resilient, with the availability of multiple routes for a message to travel. Our LoRa-based system achieves a 1–6 s warning window, slightly behind the 1.5–6.75 s of the internet-based performance of CRISiSLab’s system. Nevertheless, our novel network is effective for timely mental preparation, simple protective actions, and automation. Experiments with Lilygo LoRa32 prototype devices are presented as a practical demonstration.

This research presents an efficient fruit monitoring and orchard management system to replace the existing paper-based manual process. The new method is based on five state-of-the-art technologies, namely Radio Frequency IDentification (RFID), Wi-Fi network, Mobile App, Coud database/server, and Web Application. This paper presents the proper integration of these technologies to provide an effective, worker-friendly, and cost-effective solution to the problem. The proposed method starts by attaching RFID tags to each tree and each fruit and registering them in the cloud database. The cloud server visualizes the status of the orchard and implements inventory management. Workers use a hand device for tasks such as bagging, spraying, and plucking. The orchard manager carries out task assignments and worker deployment on the web application. Each worker gets notified of the assigned tasks on his hand …