Remotely Controlled Continuous Surveillance of Viral RNA in Wastewater Using a LoRa Network

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Authors: Aneesh Kshirsagar, Anthony J. Politza, Ming Dong, Weihua Guan
Cited by: 0
References: 46

Abstract

Tracking the rapid spread of infectious diseases such as COVID-19 in communities poses a significant global health challenge, mainly because traditional testing methods struggle to detect asymptomatic carriers and effectively manage outbreaks. To address this, we present a scalable, networked molecular testing framework for wastewater-based epidemiology that, for the first time, integrates portable nucleic acid testing (NAT) devices with long-range wireless communication and cloud-based data management. Each battery-powered node can perform Reverse Transcription - Loop-mediated Isothermal Amplification (RT-LAMP), a rapid nucleic acid amplification method, on-site directly on raw wastewater samples for SARS-CoV-2 detection. A node executes up to eight independent tests on a microfluidic cartridge, monitoring fluorescence signals from the RT-LAMP reactions in real time and transmitting the results via long-range radio (LoRa) to a gateway, which uploads structured data to a NoSQL cloud database. An interactive dashboard enables bidirectional communication with nodes and provides spatiotemporal visualization of both live and historical data, including hotspot identification through geotagging and mapping of metrics such as 7-day positivity rates. Rigorous system testing with four nodes under varied transmission scenarios confirmed a packet delivery ratio exceeding 99%, ensuring accurate and reliable reconstruction of time-series RT-LAMP curves. By integrating NAT with IoT communication and cloud analytics, this system supports unattended, long-term wastewater monitoring and can provide public health officials with timely, actionable insights. This framework demonstrates the potential of IoT-enabled molecular testing to advance decentralized surveillance beyond conventional laboratory-based workflows.

Fields of Study & Subjects

SARS-CoV-2 detection and testing Biosensors and Analytical Detection IoT Networks and Protocols

Publication details

Journal / source
IEEE Internet of Things Journal
Volume
13
Issue
6
Pages
10751–10762
Publication date
6 January 2026
Language
EN