Water quality monitoring and its use in smart agriculture and other crucial domains is an important step towards a system based on risk analysis on how data is transmitted over the network. In this article, the emphasis is on the security of the transmitted data and is based on the developed project SWAM (Smart WAter Management system for better environmental sustainability). The security services used in the current paper are based on an architecture that provides a set of security guarantees capable of mitigating certain threats relevant to the water quality monitoring system used in agriculture. These services are beneficial for irrigation system operators because the devices are authenticated, then the data is sent from the station and reaches the platform and is not modified in the sense of simulating erroneous measurements. The general purpose of the article is to describe the security aspect, elements and factors of the SWAM architecture. Security is required at all IoT levels, for example, at the device level, including sensors for water quality monitoring and communication level (generally through the Gateway).
Yu‐Pin Lin, Hussnain Mukhtar, Kuan-Ting Huang, Joy R. Petway · 7 authors
Real-time identification of irrigation water pollution sources and pathways (PSP) is crucial to ensure both environmental and food safety. This study uses an integrated framework based on the Internet of Things (IoT) and the blockchain technology that incorporates a directed acyclic graph (DAG)-configured wireless sensor network (WSN), and GIS tools for real-time water pollution source tracing. Water quality sensors were installed at monitoring stations in irrigation channel systems within the study area. Irrigation water quality data were delivered to databases via the WSN and IoT technologies. Blockchain and GIS tools were used to trace pollution at mapped irrigation units and to spatially identify upstream polluted units at irrigation intakes. A Water Quality Analysis Simulation Program (WASP) model was then used to simulate water quality by using backward propagation and identify potential pollution sources. We applied a “backward pollution source tracing” (BPST) process to successfully and rapidly identify electrical conductivity (EC) and copper (Cu2+) polluted sources and pathways in upstream irrigation water. With the BPST process, the WASP model effectively simulated EC and Cu2+ concentration data to identify likely EC and Cu2+ pollution sources. The study framework is the first application of blockchain technology for effective real-time water quality monitoring and rapid multiple PSPs identification. The pollution event data associated with the PSP are immutable.
Sina Rafati Niya, Sanjiv S. Jha, Thomas Bocek, Burkhard Stiller
This work proposes an IoT- and Blockchain-based, distributed system, for automated measuring, storing, and monitoring of water and air quality in environments such as lakes, mountains, urban areas, or factories. Comparable state-of-the-art solutions, require human interaction to access the data or require high power consumption or space requirements, or they are based on centralized architectures. The proposed pollution monitoring system here, on one hand, employs LoRa to address the high power consumption and long-range transmission challenges of IoT protocols. On the other hand, it is designed to be fully decentralized by using the Ethereum Blockchain to store and retrieve the data recorded by IoT sensors. Thus, data integrity is provided without the need for a Trusted Third Party (TTP) and data is collected and captured automatically without any manual operations needed. Observations on the four different types of sensors for measuring Potential Hydrogen (PH), Turbidity, Carbon monoxide (CO), and Carbon dioxide (CO2), revealed a high accuracy with the expected time-lines of measurements, non-falsified experimental values collected and can be used as reliable evidence of presence of pollution.
Utilities have traditionally employed or contracted meter readers to collect natural gas usage data, which is expensive and time consuming, and thus necessitates the need of smart natural gas metering. Existing gas metering systems mainly focus on measuring the amount of gas flowing through an microelectro mechanical system (MEMS) thermal gas flow sensor and simply ignore the detailed gas composition. From computational fluid mechanics simulations, however, we discover that gases with different compositions will cause different effects on the reading of an MEMS sensor. Based on a thorough analysis of the working principle of MEMS thermal gas flow sensor, we propose an innovative mechanism to compensate the errors caused by different types of natural gases on the sensor's reading. The proposed solution first measures the physical property of metered gas to derive the composition correction coefficient that will then be used to correct the meter's reading errors, considering the relation between the calorific value and physical property of natural gases. In this way, the proposed solution realizes a real-time multicomposition gas metering via thermal gas flow sensors. We implement and evaluate the proposed gas metering technique in various Internet of Things systems, including industrial flow metering, gas metering in smart home, and gas metering in low-power wide-area networks. Experiment results verify the innovative design and confirm that the proposed solution features high sensitivity, high precision, and high range ratio.
Nov 10, 2015·2015 ASABE / IA Irrigation Symposium: Emerging Technologies for Sustainable Irrigation - A Tribute to the Career of Terry Howell, Sr. Conference Proceedings
Abstract. Modern flow metering technology frequently emphasizes the exploitation of ultrasonics, communications, and other electronic-based systems. Yet, there are thousands of irrigation measurement locations that are poorly served by existing devices. Even the more sophisticated developments are limited, for indeed, neither one-size nor one-method fits all. Discussed are hydraulic principles and flow measurement methodologies that are economical, convenient, and accurate. Some are common knowledge and some not-so-common, but all contribute to managing our water-resources. Some improvements in older techniques are often supported by improvements in communications and computer software. Improved broader understanding of hydraulics contributes to convenient flume and weir zero registration, stilling well design modifications, and accurate sediment-sampler design methods. The sampler concepts can also be applied to sprinkler-nozzle testing and to rain-gage accuracy. Additionally, weed-proofing of propeller meters and cone meters without weed screening is discussed.