Xinyao Chen

Bio: Xinyao Chen is an academic researcher from Chongqing Technology and Business University. The author has contributed to research in topics: Decision support system. The author has an hindex of 1, co-authored 1 publications receiving 3 citations.

Data-driven peer-to-peer blockchain framework for water consumption management

Abstract: It is widely believed that effective water resource management can optimize the scheduling of water supply plans, which is essential for sustainable development. The core of management is to accurately predict future water consumption. However, existing studies generally face two challenges. First, a reliable bottom platform for the support of online data integration is absent. In addition, multisource factors that primarily affect water consumption are neglected when modeling. To solve the above problems, this paper proposes a data-driven peer-to-peer blockchain framework to predict water consumption. Fundamentally, it utilizes a blockchain system with a peer-to-peer network to serve as the decision support platform hardware. On this basis, an intelligent prediction algorithm that combines the grey model and long short-term memory model is developed to drive the hardware infrastructure. After that, the performance of the proposed method is evaluated by carrying out experiments on a real-world dataset, and three typical approaches are selected for comparison. The experimental results show that the proposal exceeds general prediction models by approximately 8%.

A Framework of Blockchain Technology in Intelligent Water Management

Abstract: At present, water resource information management in China is mainly a centralized model, and there exist some problems such as high cost, low efficiency, and data storage insecurity. Blockchain technology provides a good solution which can create an efficient trust mechanism among the links in the process of water resource utilization. It guarantees the security of the data, avoiding the sudden collapse of the central institutions caused by some normal operations of the entire system. Based on a decentralization blockchain, we propose a decentralized water resource information management system for the whole process of “supply-use-consumption-discharge,” which improves the traditional water data storage. Specifically, the monitoring and business data are encrypted by the blockchain and are transmitted using a peer-to-peer network. Moreover, the centralized management mode is changed and part of the management work is dispersed to each node. Thus, decisions and measures can be made and implemented quickly after discovering problems to improve the efficiency of information transmission and management. In addition, two typical blockchain-based application scenarios for water resource management are designed. A blockchain-based approach makes issuing and monitoring water abstraction permits more convenient and obtaining license information more secure and verifiable. A reliable mechanism for tracing water quality ensures the accuracy and reliability of water quality information, enables the detection of locations with inadequate water quality, and clarifies people’s responsibility, thus guaranteeing the water safety of the residents.

Prediction of Water Consumption in 31 Provinces of China Based on FGM(1,1) Model

Abstract: Human production activities and social development cannot be separated from the indispensable water resources. In recent years, with the increasing speed of China's economic development, the consumption of water resources has gradually become the focus of attention of the Chinese government and the public. Based on the original data of water use of 31 provinces (municipalities and autonomous regions) in China from 2014 to 2018, a fractional order accumulative gray prediction model (FGM(1,1)) is established to predict the water use of 31 provinces (municipalities and autonomous regions) in China in the short term, and the applicability of the model is verified by the mean absolute percentage error (MAPE) value. According to the MAPE value, the data obtained by the FGM(1,1) model is relatively accurate. The prediction results show that in case of little change in total water consumption, agricultural water and industrial water use show a downward trend, while domestic water use shows an upward trend. The government's water management policy for urban residents needs to be adjusted, and the publicity work to improve the water-saving awareness of urban residents needs to be improved.

Application of Distributed Ledger Platforms in Smart Water Systems—A Literature Review

Abstract: The application of distributed ledger technologies, including blockchain, is rapidly growing in governance, transport, supply chain, and logistics. Today, blockchain technology is promoted as the heart of Smart Cities. This study reviews the potential of blockchain application in water management systems. We surveyed the literature and organized the previous studies based on three main application topics: Smart Water Systems, Water Quality Monitoring, and Storm Water Management. Also, we addressed technical, organizational, social, and institutional challenges that may hinder the adoption of Blockchain technology. Water management systems need to have a long-term commitment plan, update their organizational policies, and acquire relevant knowledge and expertise before successfully adopting any distributed ledger technology.