Wireless sensor networks for agriculture

Development in the technology of sensor such as Micro Electro Mechanical Systems (MEMS), wireless communications, embedded systems, distributed processing and wireless sensor applications have contributed a large transformation in Wireless Sensor Network (WSN) recently. It assists and improves work performance both in the field of industry and our daily life. Wireless Sensor Network has been widely used in many areas especially for surveillance and monitoring in agriculture and habitat monitoring. Environment monitoring has become an important field of control and protection, providing real-time system and control communication with the physical world. An intelligent and smart Wireless Sensor Network system can gather and process a large amount of data from the beginning of the monitoring and manage air quality, the conditions of traffic, to weather situations. In this paper, we discuss and review wireless sensor network applications for environmental monitoring. In order to implement a good monitoring system, there are several requirements to be followed. From the studies, it has been proved to be an alternative way to replace the conventional method that uses men force to monitor the environment. It is also proven that these approaches can improve the system performance, provide a convenient and efficient method and can also fulfill functional requirements.

Wireless Sensor Network Applications: A Study in Environment Monitoring System

Structural health monitoring at local and global levels using computer vision technologies has gained much attention in the structural health monitoring community in research and practice. Due to t...

A review of computer vision–based structural health monitoring at local and global levels:

Smart cities contain intelligent things which can intelligently automatically and collaboratively enhance life quality, save people's lives, and act a sustainable resource ecosystem. To achieve these advanced collaborative technologies such as drones, robotics, artificial intelligence, and Internet of Things (IoT) are required to increase the smartness of smart cities by improving the connectivity, energy efficiency, and quality of services (QoS). Therefore, collaborative drones and IoT play a vital role in supporting a lot of smart-city applications such as those involved in communication, transportation, agriculture,safety and security, disaster mitigation, environmental protection, service delivery, energy saving, e-waste reduction, weather monitoring, healthcare, etc. This paper presents a survey of the potential techniques and applications of collaborative drones and IoT which have recently been proposed in order to increase the smartness of smart cities. It provides a comprehensive overview highlighting the recent and ongoing research on collaborative drone and IoT in improving the real-time application of smart cities. This survey is different from previous ones in term of breadth, scope, and focus. In particular, we focus on the new concept of collaborative drones and IoT for improving smart-city applications. This survey attempts to show how collaborative drones and IoT improve the smartness of smart cities based on data collection, privacy and security, public safety, disaster management, energy consumption and quality of life in smart cities. It mainly focuses on the measurement of the smartness of smart cities, i.e., environmental aspects, life quality, public safety, and disaster management.

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Survey on Collaborative Smart Drones and Internet of Things for Improving Smartness of Smart Cities

Wireless Sensor Networks (WSNs) are spatially scattered independent sensors to track physical objects or monitor environmental data and collectively transmit the data to master station. WSN is deployed in numerous fields such as animal tracking, precision agriculture, environmental monitoring, security and surveillance, smart buildings, health care and so on. This paper presents various applications of WSN with the intention of disseminating various applications of WSN for the better understanding of the research community to apply WSN in further innovative fields.

Applications of wireless sensor networks — A survey

Wireless sensor network-based fire detection, alarming, monitoring and prevention system for Bord-and-Pillar coal mines

Extended digital image correlation method for analysis of discrete discontinuity

Fire is of major concern to those who work in underground coal mines. It is important to have a warning system that is capable of detecting fire and generating an alarm. In this paper, we present the design of an early warning system in a “Bord & Pillar” coal mine. It uses Wireless Sensor Networks (WSN) to detect the exact fire location and spreading direction and also provide the fire prevention system to stop the spread of fire to save the natural resources and the mining personnel from fire. Simulation analysis results show that the average network delay varies almost linearly with the increase in the number of hops.

Fire monitoring in coal mines using Wireless Sensor Networks

Finite-element-based digital image correlation (FEM-DIC) is one of the most widely used noncontact techniques in the field of experimental mechanics for measurement of deformation/strain. In this paper, the FEM-DIC method is refined by introducing the concept of multilevel extended digital image correlation (X-DIC), which also can capture deformation across discontinuity planes if they exist in images. Using regular and enhanced displacements at each node, strain tensors are estimated by applying the concept of smooth particle hydrodynamics (SPH). Numerical works are carried out to check the accuracy level of the developed algorithm by considering discrete discontinuity on the surface of a sample. Work is further extended to determine displacements and strains developed at the surface of several cubical concrete samples under uniaxial loading conditions. The tests are conducted until fractures are developed in the post-failure region. Using the concept of cumulative effective strain, a parameter is identified, which can be used as a precursor in the object failure process.

Sudipta Bhattacharjee

Papers

Wireless sensor network-based fire detection, alarming, monitoring and prevention system for Bord-and-Pillar coal mines

Extended digital image correlation method for analysis of discrete discontinuity

Fire monitoring in coal mines using Wireless Sensor Networks

Optical strain for monitoring of concrete failure mechanism with discontinuity.

Automatic detection and classification of damage zone(s) for incorporating in digital image correlation technique