Industries, household communities consume a lot of water on regular basis, thereby increasing water crisis. There is continuous increase in water consumption by industries. Reusing wastewater can reduce water withdrawals from local water sources thus increasing water availability, lowering wastewater discharges and their pollutant load, reducing thermal energy consumption and, potentially, processing cost. Various ways have been implemented for recycling the generated wastewater. Wastewater must be reused for the benefit of mankind. In this paper we propose a wastewater recycle control system to efficiently manage the wastewater and coordinate it among the industries and the government. Blockchain technology has been deployed for storing data and developing an incentive model to encourage wastewater reuse. Tokens are provided to industries in proportion to quantity and quality of reused wastewater. Rules for issue and trade of these tokens are written as a smart contract. Unfortunately, providing such incentives also provides a motive for tampering the data on which these tokens are awarded. Anomaly detection algorithms are used to detect the potential frauds which take place in the system upon IoT meter data tampering. The system uses IoT meters that measure volume of wastewater generated and reused, along with quality metrics such as pH, hardness and oil content. Multiple machine learning algorithms are used to detect tampering- polynomial regression, DBSCAN, autoencoders and LSTM networks. Their performance has then been compared. A first implementation of this system and an evaluation of the system's performance are also presented.
Iyer et al. (Mon,) studied this question.