Please use this identifier to cite or link to this item: http://dspace.iitrpr.ac.in:8080/xmlui/handle/123456789/3498
Title: TEMPSENSE: LoRa Enabled Integrated Sensing and Localization Solution for Water Quality Monitoring
Authors: Baghel, L.K.
Gautam, S.
Malav, V.K.
Kumar, S.
Keywords: Hardware design
Internet of Things (IoT)
localization
long range (LoRa)
water quality monitoring
Issue Date: 19-Jun-2022
Abstract: With the continuous increase in water pollution, water quality monitoring has become quite essential. Though existing solutions facilitate various features [e.g., the potential of hydrogen (pH), dissolved oxygen (DO), temperature, and electrical conductivity (EC)], they possess numerous limitations: 1) most of the existing systems rely on regional wireless systems, e.g., global system for mobile communication (GSM) and a global positioning system (GPS); hence, their performance varies with local connectivity and 2) usually, the setup is deployed at remote locations, including river site, so the solutions need to be power-optimized and should be able to support self-localization ability, which lacks the existing solutions. In this context, we have developed a cost-effective functionality integration that brings different sensors, processing units, and Long Range (LoRa) transmission to a single platform, providing a compact, power-efficient, and low-cost Total dissolved solids (TDS), Ec, teMperature, pH monitoring SystEm with integrated localizatioN Solution (TEMPSENSE). The proposed TEMPSENSE hardware is equipped with interactive sensing and localization algorithms that address the abovementioned concerns and facilitate the real-time location along with the required water quality parameters. Also, the proposed system has been thoroughly investigated by designing the hardware at the institution’s laboratory. Furthermore, it is shown that the proposed hardware is several times cheaper than the available industrial solutions. Moreover, a number of experiments on different types of solutions have been performed for validation of the proposed design. Furthermore, extensive experiments have been performed for localization in low- and high-density scenarios and are found that the proposed algorithm is potentially able to estimate the real-time location of the TEMPSENSE.
URI: http://localhost:8080/xmlui/handle/123456789/3498
Appears in Collections:Year-2022

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