Improving Geo-Location Performance of LoRa with Adaptive Spreading Factor

The Low-Power Long-Range Wide Area Network (LoRaWAN) technology has received considerable attention in recent years with a wide-range of emerging applications such as precision agriculture, tracking, home security, water, and air pollution monitoring, among many others. One of the potential use cases of the LoRa technology is the geo-location of people with cognitive problems (autism spectrum disorder, Down syndrome, dementia) that could alleviate one of the biggest concerns of caregivers on how to prevent their patients wandering from their safe settings. While existing commercially available personal tracking devices can help locate missing persons, most of them are expensive (cellular subscriptions and/or high monthly service fees associated with one-to-one communication between child/patient and parent/provider), rely solely on global positioning system that does not work well in indoors, have limited coverage (if based on Bluetooth or Wi-Fi access) as well as poor battery life (require frequent recharging). Moreover, current LoRaWAN solutions also suffer from coverage and packet loss issues in dense environments (e.g., indoors, or outdoors with dense buildings or blockages). While a higher spreading factor can improve the communication range, but it will also result in a lower transmission bit rate which is a critical design consideration owing to the over-the-airtime restrictions of such LoRa networks. In this work, we propose and implement an adaptive algorithm in a LoRaWAN testbed that will dynamically change the spreading factor based on the received signal strength indicator (RSSI), packet SNR, and/or packet success rate to improve the overall coverage and throughput of the network. This in turn will translate into a better and economically feasible tracking/geo-location solution. Our proposed solution will give a peace of mind to caregivers at an affordable price aside from mitigating “caregiver burnout syndrome” and/or preventing the need for resource-intensive search-and-rescue efforts.