Modeling and evaluation of quality monitoring based on wireless sensor and blockchain technology for live fish waterless transportation

2022 ◽  
Vol 193 ◽  
pp. 106642
Author(s):  
Huanhuan Feng ◽  
Mengjie Zhang ◽  
Valentina Gecevska ◽  
Bingqi Chen ◽  
Rehan Saeed ◽  
...  
Author(s):  
José Jasnau Caeiro ◽  
João Carlos Martins

Internet of Things (IoT) systems are starting to be developed for applications in the management of water quality monitoring systems. The chapter presents some of the work done in this area and also shows some systems being developed by the authors for the Alentejo region. A general architecture for water quality monitoring systems is discussed. The important issue of computer security is mentioned and connected to recent publications related to the blockchain technology. Web services, data transmission technology, micro web frameworks, and cloud IoT services are also discussed.


2021 ◽  
Vol 7 ◽  
pp. e711
Author(s):  
Truong Van Truong ◽  
Anand Nayyar ◽  
Mehedi Masud

In this paper, we study the air quality monitoring and improvement system based on wireless sensor and actuator network using LoRa communication. The proposed system is divided into two parts, indoor cluster and outdoor cluster, managed by a Dragino LoRa gateway. Each indoor sensor node can receive information about the temperature, humidity, air quality, dust concentration in the air and transmit them to the gateway. The outdoor sensor nodes have the same functionality, add the ability to use solar power, and are waterproof. The full-duplex relay LoRa modules which are embedded FreeRTOS are arranged to forward information from the nodes they manage to the gateway via uplink LoRa. The gateway collects and processes all of the system information and makes decisions to control the actuator to improve the air quality through the downlink LoRa. We build data management and analysis online software based on The Things Network and TagoIO platform. The system can operate with a coverage of 8.5 km, where optimal distances are established between sensor nodes and relay nodes and between relay nodes and gateways at 4.5 km and 4 km, respectively. Experimental results observed that the packet loss rate in real-time is less than 0.1% prove the effectiveness of the proposed system.


2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Xiong Yang ◽  
Yuling Chen ◽  
Xiaobin Qian ◽  
Tao Li ◽  
Xiao Lv

The distributed deployment of wireless sensor networks (WSNs) makes the network more convenient, but it also causes more hidden security hazards that are difficult to be solved. For example, the unprotected deployment of sensors makes distributed anomaly detection systems for WSNs more vulnerable to internal attacks, and the limited computing resources of WSNs hinder the construction of a trusted environment. In recent years, the widely observed blockchain technology has shown the potential to strengthen the security of the Internet of Things. Therefore, we propose a blockchain-based ensemble anomaly detection (BCEAD), which stores the model of a typical anomaly detection algorithm (isolated forest) in the blockchain for distributed anomaly detection in WSNs. By constructing a suitable block structure and consensus mechanism, the global model for detection can iteratively update to enhance detection performance. Moreover, the blockchain guarantees the trust environment of the network, making the detection algorithm resistant to internal attacks. Finally, compared with similar schemes, in terms of performance, cost, etc., the results prove that BCEAD performs better.


Author(s):  
Imrich Andras ◽  
Linus Michaeli ◽  
Jan Saliga

This work presents a novel unconventional method of signal reconstruction after compressive sensing. Instead of usual matrices, continuous models are used to describe both the sampling process and acquired signal. Reconstruction is performed by finding suitable values of model parameters in order to obtain the most probable fit. A continuous approach allows more precise modelling of physical sampling circuitry and signal reconstruction at arbitrary sampling rate. Application of this method is demonstrated using a wireless sensor network used for freshwater quality monitoring. Results show that the proposed method is more robust and offers stable performance when the samples are noisy or otherwise distorted.


2017 ◽  
Vol 11 (3) ◽  
pp. 301-311 ◽  
Author(s):  
Volker Skwarek

Purpose This paper aims to describe a method for Internet-of-Things-devices to achieve industrial grade reliability for information transfer from wireless sensor systems to production systems using blockchain technologies. Design/methodology/approach An increased security and reliability of submitted data within the sensor network could be achieved on an application level. Therefore, a lightweight, high-level communication protocol based on blockchain principles was designed. Findings Blockchain mechanisms can secure the wireless communication of Internet-of-Things-devices in a lightweight and scalable manner. Originality/value The innovation of this research is the successful application of general blockchain mechanisms to increase security of a wireless sensor system without binding to a dedicated blockchain technology.


Water ◽  
2020 ◽  
Vol 12 (4) ◽  
pp. 1096 ◽  
Author(s):  
Ramón Martínez ◽  
Nuria Vela ◽  
Abderrazak el Aatik ◽  
Eoin Murray ◽  
Patrick Roche ◽  
...  

The deteriorating water environment demands new approaches and technologies to achieve sustainable and smart management of urban water systems. Wireless sensor networks represent a promising technology for water quality monitoring and management. The use of wireless sensor networks facilitates the improvement of current centralized systems and traditional manual methods, leading to decentralized smart water quality monitoring systems adaptable to the dynamic and heterogeneous water distribution infrastructure of cities. However, there is a need for a low-cost wireless sensor node solution on the market that enables a cost-effective deployment of this new generation of systems. This paper presents the integration to a wireless sensor network and a preliminary validation in a wastewater treatment plant scenario of a low-cost water quality monitoring device in the close-to-market stage. This device consists of a nitrate and nitrite analyzer based on a novel ion chromatography detection method. The analytical device is integrated using an Internet of Things software platform and tested under real conditions. By doing so, a decentralized smart water quality monitoring system that is conceived and developed for water quality monitoring and management is accomplished. In the presented scenario, such a system allows online near-real-time communication with several devices deployed in multiple water treatment plants and provides preventive and data analytics mechanisms to support decision making. The results obtained comparing laboratory and device measured data demonstrate the reliability of the system and the analytical method implemented in the device.


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