Wireless Sensor Network-based Monitoring System Research Articles

Wireless Sensor Network-based Monitoring System for Health Structure of Rail-tracks: An Efficient Design for Communication

The paper introduces a monitoring system for the health structure of rail-tracks. The slab track system is highly demanded due to its quality for safety measures and highly sustainable quality for high-speed railway infrastructure, particularly in India for the Bullet-train project. Previously, the system used to monitor the health of slab-tracks was costly and not done regularly, but the evolution of digitalization and wireless sensor networks is doing tremendous work for monitoring the health of infrastructure and other activities. In rail-track systems, wireless sensors can provide us with information, detection, and prediction of the health-infrastructure of rail-tracks. An efficient design for communication systems is needed for such safety-critical railway tracks. The paper proposes an accurate and efficient design for communication.

A wireless sensor network-based monitoring system for freshwater fishpond aquaculture

Cabled intelligent systems bring with them the complexities of structures, the complications of data measurements and transmission, and a limited scale of application. A wireless sensor network is used to eliminate these disadvantages, however reliability of data transmission and energy saving in a wireless sensor network are two challenges that still need to be addressed. The design information on three types of nodes in a wireless sensor network is described in detail. Tree topology for WSN is adopted to decrease the packet loss rate and improve reliability of data transmission. Allowing sensor nodes to sleep and reorganising the data frames are the two approaches used to achieve energy-saving. The experimental results demonstrate the usefulness of these approaches in solving the challenges.

A wireless sensor network-based monitoring system with dynamic convergecast tree algorithm for precision cultivation management in orchid greenhouses

The orchid industry in Taiwan has established large-scale orchid greenhouses to achieve high-precision cultivation of orchids, especially for Phalaenopsis. The wireless sensor network (WSN) technology has been shown to be able to play an important and useful role for effectively acquiring environmental parameters in real-time. However, the mobile benches equipped with different sensors used in an orchid greenhouse create a problem of susceptible dynamic network topology. To meet the requirements of reliable data acquisition in the monitoring of orchid growth, a novel dynamic convergecast tree algorithm (DCTA) based on a tree-like topology was designed and implemented in the WSN-based monitoring system. The proposed WSN algorithm uses the information of the received signal strength indication and hop count to dynamically adjust the routing path of each sensor node. The proposed algorithm includes a flexible scheduling-based design for the medium access control protocol to guarantee higher transmission reliability of the sensor data. An extensive series of experiments, including tests in the lab and an orchid greenhouse, were conducted to examine the performance of the proposed DCTA. The experimental results show that the proposed algorithm can reliably collect environmental data; average successful data delivery rates up to 92.5 % of the entire tested networks with multiple mobile nodes in the greenhouse can be achieved. The WSN-based monitoring system equipped with the proposed DCTA provides environmental measurements with better spatio-temporal resolution to achieve precision cultivation management for orchids.

Hammerstein-Wiener model for the prediction of temperature variations inside silage stack-bales using wireless sensor networks

Animal forage plays an important role in agriculture. To maintain the silage quality during storage, preserving it from decomposition by wrapping the harvested crop with plastic stretch film is crucial. Any failure in the preserving process permits the infusion of oxygen, which allows the growth of undesirable aerobic microorganisms and silage decomposition. To study the state of the silage, temperature inside the stack could be used as indicator of decomposition. However, no previous study has developed a model that can detect decomposition based on abnormal temperature variations inside a silage stack. The first objective of this paper was to develop a structured nonlinear model to estimate the dynamics of temperature variations measured by a wireless sensor network-based monitoring system (nRF95E) inside a silage bale and stack prior to the decomposition process. The requirement of a robust nonlinear model is that sensor nonlinearities that are inherent in nature are considered. The results showed that a Hammerstein-Wiener (HW) model with sigmoid network performed the best in terms of percentage of fit (91.70%) between the measured and simulated output. The second objective was to estimate the length of time required to detect the decomposition process after the airtight seal was punctured using the model. The error between the predicted model output and the sensor readings exceeded a preset threshold interval 17 days after the cover film was punctured and 9 days after the decomposition process was detected due to the odour released.

Energy generation for an ad hoc wireless sensor network-based monitoring system using animal head movement

The supply of energy to electronics is an imperative constraining factor to be considered during the design process of mobile ad hoc wireless sensor networks (MANETs). This influence is especially important when the MANET is deployed unattended or the wireless modules within the MANET are not easily accessible. Therefore, exploring novel sources of energy generation rather than operating electronics only on limited power supplies such as batteries is a major challenge. Monitoring free-ranging animal behavior is an application in which the entities (animals) within the MANET are not readily accessible; however, animal movement can be potentially used to generate energy. In this study, the head movements of individual sheep in a flock during grazing were monitored in order to investigate the amount of energy that can be generated by these movements. By applying the Lagrange–d’Alembert Principle to this problem, the equations of motion from each neck-mounted sensor as well as the amount of mechanical energy generated per time instant (each second) during upward and downward head movements were calculated. This resulted in the production of 857 mW and 1660 mW during the downward and upward movements, respectively. Furthermore, the energy consumption of each wireless node within the MANET was estimated to be 117.8 mW per second. Conversion of energy from mechanical to electrical requires miniature electromechanical generators that can currently provide between 25% and 50% conversion efficiency. Even using the worst conversion efficiency (25%), a minimum of 214 ± 25 mW of electrical energy per second could be generated. This amount exceeds the energy consumed by the wireless sensors that can be used to gather parameters describing animal behavior such as neck and head movement. This study suggests that the amount of energy generated by the vertical neck–head movement of sheep during grazing can be converted to useful electrical power adequate to provide power for operation of wireless sensor nodes on a continuous basis within a MANET-based animal behavior monitoring system.