Utilization Of Wireless Sensor Networks Research Articles

A proposed plant classification framework for smart agricultural applications using UAV images and artificial intelligence techniques

Utilizing Wireless Sensor Networks (WSNs), Internet of Things (IoTs) sensors, and Unmanned Aerial Vehicles (UAVs), in conjunction with optimization techniques and machine learning algorithms, can present a novel approach to Precision Agricultural (PA) crops. Agriculture has transitioned from traditional legacy systems to incorporate advanced smart technologies. Several complex farming problems are utilized to promote a variety of UAV sensing and Artificial Intelligence (AI) algorithms in PA applications of smart agriculture, especially in developing countries. This paper proposes the design of a conceptual UAV sensing system for crop management using a novel classification framework. UAV-based image datasets can be implemented and expanded to various types of crops. In addition, it can classify various types of rice species and detect weed farms as it consists of a multistage process for identifying and monitoring different crops. The proposed classification framework is evaluated using three different real UAV image datasets compared with Naive Bayes, Decision Tree (DT), Bagging, and Random Forest (RF) techniques. The classification performance metrics obtained are as follows: i) the WeedNet dataset with 100 % F1-score, 100 % recall, 100 % precision, and 100 % accuracy; ii) the Rice Seedling dataset with 99.5 % F1-score, 99.5 % recall, 99.5 % precision, and 99.5 % accuracy; and iii) the Rice Varieties dataset with 97.99 % F1-score, 97.99 % recall, 98.14 % precision, and 97.99 % accuracy. The success rates achieved by the proposed classification framework outperform those of other recent state-of-the-art techniques, demonstrating its efficacy in crop management applications.

Wireless Sensor Placement Optimization for Bridge Health Monitoring: A Critical Review

In recent years, wireless sensors have progressively supplanted conventional limited sensors owing to their attributes of small size, low cost, and high accuracy. Consequently, there has been a growing interest in leveraging wireless sensor networks for bridge structural health monitoring applications. By employing wireless sensor nodes to gather data from various segments of the bridge, information is relayed to a signal-receiving base station. Subsequently, the health status of the bridge is inferred through specific data processing and analysis, aiding monitoring personnel in making informed decisions. Nonetheless, there are limitations in this research, particularly pertaining to power consumption and efficiency issues in data acquisition and transmission, as well as in determining the appropriate wireless sensor types and deployment locations for different bridge configurations. This study aims to comprehensively examine research on the utilization of wireless sensor networks in the realm of bridge structural health monitoring. Employing a systematic evaluation methodology, more than one hundred relevant papers were assessed, leading to the identification of prevalent sensing techniques, data methodologies, and modal evaluation protocols in current use within the field. The findings indicate a heightened focus among contemporary scholars on challenges arising during the data acquisition and transmission processes, along with the development of optimal deployment strategies for wireless sensor networks. In continuing, the corresponding technical challenges are provided to address these concerns.

Enhancing K-Nearest Neighbors Algorithm in Wireless Sensor Networks through Stochastic Fractal Search and Particle Swarm Optimization

The utilization of wireless sensor networks (WSNs) holds significant importance in diverse data collection applications. Efficient operation of computers, especially in predictive tasks, is imperative for obtaining accurate results within WSNs. This research introduces an innovative approach employing Stochastic Fractal Search-Particle Swarm Optimization (SFS-PSO) to enhance the performance of the K-Nearest Neighbors (KNN) algorithm. The proposed methodology initiates with the establishment of a particle population, dynamically adjusting their positions and velocities and integrating a diffusion process. Through an iterative process of incremental adjustments and evaluations, the algorithm fine-tunes its parameters, resulting in a refined KNN regression model. The enhanced model exhibits substantial improvements, as indicated by the notable reduction in root mean square error (RMSE) and mean absolute error (MAE), accompanied by a strengthened correlation between variables. The favorable outcomes underscore the efficacy of the SFS-PSO optimization technique in augmenting the KNN algorithm's performance within wireless sensor networks. In simpler terms, the application of SFS-PSO in conjunction with KNN leads to a significant decrease in RMSE, reaching a value as low as 0.00894, demonstrating the notable effectiveness of this optimization approach in refining the predictive capabilities of the KNN algorithm in the context of WSNs.

Metaheuristic algorithm for energy efficient clustering scheme in wireless sensor networks

The utilization of wireless sensor networks (WSNs), which combine sensing, communication, and computation in an intelligent environment. The use of energy becomes the primary obstacle for sensor nodes to overcome. Clustering and routing algorithms are promising ways to fix the issue and prolong the network's effectiveness. The availability of restricted energy resources is the most significant challenge in WSNs. In this paper, we propose an energy-efficient clustering scheme integrated with a particle swarm optimization method called PSO-EECS for wireless sensor networks to raise energy efficiency while simultaneously increasing the lifetime of sensor nodes. The predominant concern being addressed in this paper is the selection of a Cluster Head (CH), which helps gather, aggregate and forward the data from the cluster-based routing paradigm. PSO-EECS algorithm is used to optimize the fitness parameters for CH selection, which include the energy ratio, distance considerations, node density, load balancing, and the Network's average energy, among other things. The simulation results reveal that the proposed technique offers a considerable improvement in network stability and operation time compared to the currently used approaches. Compared to the PSOGSA, GAPSOH, and ABE-DE protocol, simulation findings demonstrate that PSO-EECS enhances stability by 95.4%, 34.8%, and 29.2%, respectively.

A Novel LoRa-Based Platform for Remote Monitoring of Large-Scale Rice Fields

The utilization of wireless sensor networks is widespread across numerous industries, including smart agriculture, where the need to remotely monitor agricultural production environments on a large scale is imperative for improving farm product quality and preserving the ecosystem. In this paper, a novel and efficient wireless sensor network framework is presented, which employs LoRa technology to facilitate remote environmental monitoring during agricultural cultivation. Our proposed network framework possesses the capability of long-range data transmission, secure data transfer from source nodes to gateway, high reliability, and easy deployment for large-scale farm monitoring applications. The effectiveness of our model was evaluated in An Giang province, Vietnam, with monitoring indicators encompassing temperature, air humidity, soil moisture, pH of water, CH4, and NH3. The findings reveal that the wireless sensor network model for remote monitoring of the rice cultivation environment fulfills the requirements of good and complete data transmission, high data network security, and a long signal transmission distance of up to 3.5 km at a reasonable cost.

Survey on Various Aspects of Clustering in Wireless Sensor Networks Employing Classical, Optimization, and Machine Learning Techniques

A wide range of academic scholars, engineers, scientific and technology communities are interested in energy utilization of Wireless Sensor Networks (WSNs). Their extensive research is going on in areas like scalability, coverage, energy efficiency, data communication, connection, load balancing, security, reliability and network lifespan. Individual researchers are searching for affordable methods to enhance the solutions to existing problems that show unique techniques, protocols, concepts, and algorithms in the wanted domain. Review studies typically offer complete, simple access or a solution to these problems. Taking into account this motivating factor and the effect of clustering on the decline of energy, this article focuses on clustering techniques using various wireless sensor networks aspects. The important contribution of this paper is to give a succinct overview of clustering.

Optimized power and water allocation in smart irrigation systems

Agriculture has a significant role in countries’ economy, but irrigation process consumes both power and water resources. Since in agriculture the goal is to maximize crop’s yields with minimize costs, it is important to design a national smart irrigation system with optimal allocation of power and water resources especially in a plantation area with little rains. In this work, an optimized on-demand smart irrigation system is proposed to manage the allocation of the consumed power and water in agriculture field. The system controls irrigation process by utilizing Wireless Sensor Network (WSN) to collect real-time data from the field using sensors. Raspberry pi takes appropriate decision about irrigation process according to received data from sensor nodes, and commands are sent from it to actuator nodes. Secured Message Queuing Telemetry Transport (MQTT) protocol with Transport Layer Security (TLS) authentication protocol is used in managing the data exchange in the network over Wi-Fi technology. In addition, an optimal power and water consumptions formula is derived using Lagrange Multiplier method to allocate resources in an optimal way depending on watering demands. Both theoretical and practical results approve the efficiency of the proposed system in managing irrigation process optimally.

A Wireless Communication Network With a Ballistocardiography Experiment on the ISS: Scenario, Components and Preflight Demonstration

This paper introduces Wireless Compose-2 (WICO2), which is an experiment for the International Space Station (ISS) in order to demonstrate the provision of a flexible and adaptable wireless network infrastructure integrated into a commodity item to conduct and execute low-power, low-weight and wireless experiments in the scientific and medical domain. Recent work revealed a great potential in utilizing Wireless Sensor Network (WSN) in space habitats; however, the focus was only placed on sensing in the narrowband Industrial Scientific and Medical (ISM) 2.45 GHz band. This work extends these capabilities by utilizing Impulse Radio Ultra Wideband (IR-UWB) for ranging and evaluates the use of internal light sources for energy harvesting to drive the sensor nodes. The focus of the WICO2 experiment is on the operation of the scientific experiment Ballistocardiography for Extraterrestrial Applications and long-Term missions (BEAT), which is a demonstration of novel Ballistocardiography (BCG) sensors to monitor important cardiovascular parameters in a microgravity environment. Integrated in a Smart-Shirt, it will form a Body Area Network and make use of the IR-UWB communication to transmit the data to the network. This paper describes the concept and pre-flight test results to demonstrate the correct function, usability and performance of WICO2.

Utilization of Wireless Sensor Network to Monitor Citarum River Quality for Milkfish Cultivation in Karawang Regency

The purpose of this research (study) is to demonstrate the superiority of the wireless sensor network (WSN) technology method over the laboratory method in monitoring the water quality of the Citarum River in Karawang. To monitor the Citarum river water quality, government of Karawang regency conducted a test by taking the sample water to the laboratory. It seems to be such a conventional method. With the results of the BOD value obtained from the DLHK data, which is 47.93 mg/L, of course it will be a problem for the development of milkfish. However, an advanced method using Wireless Sensor Network (WSN) technology seems to be an alternative. Basically, this technology can monitor the water quality in real-time using multiple parameters and help cultivators to monitor the water used in milkfish cultivation. Of course WSN technology is more efficient than waiting for laboratory results. Therefore, if this technology is applied, the data will be obtained in real time. Of course the data can be processed and monitored directly to determine the quality of the water used. In terms of cost, this technology can be built at a moderate cost compared to laboratory work.

IoT Based Smart Water Quality Monitoring: Recent Techniques, Trends and Challenges for Domestic Applications

Safe water is becoming a scarce resource, due to the combined effects of increased population, pollution, and climate changes. Water quality monitoring is thus paramount, especially for domestic water. Traditionally used laboratory-based testing approaches are manual, costly, time consuming, and lack real-time feedback. Recently developed systems utilizing wireless sensor network (WSN) technology have reported weaknesses in energy management, data security, and communication coverage. Due to the recent advances in Internet-of-Things (IoT) that can be applied in the development of more efficient, secure, and cheaper systems with real-time capabilities, we present here a survey aimed at summarizing the current state of the art regarding IoT based smart water quality monitoring systems (IoT-WQMS) especially dedicated for domestic applications. In brief, this study probes into common water-quality monitoring (WQM) parameters, their safe-limits for drinking water, related smart sensors, critical review, and ratification of contemporary IoT-WQMS via a proposed empirical metric, analysis, and discussion and, finally, design recommendations for an efficient system. No doubt, this study will benefit the developing field of smart homes, offices, and cities.

A Novel Groundwater Resource Forecasting Technique for Cultivation Utilizing Wireless Sensor Network (WSN) and Machine Learning (ML) Model

Groundwater is almost essential part of cultivation process, particularly in parched regions. The prophecy of groundwater intensity is crucial for understanding groundwater availability and provide systematic assistance for the cultivator that the stable convention of groundwater resource. A proposed efficient technique (ET) of forecasting the groundwater level (WFC) methodology was recognized in this study to precisely forecast groundwater intensity for cultivation in the parched regions of south India. Pumping facility, recharge capability of bore wells, exposure of cultivation area and weather conditions are used as key parameters, whereas groundwater level was considered as an output factor. The lack of systematic assistance about the groundwater availability also causes a decrease in the farmer’s emotional stability and thereby affects their plan of enlightening the right crops and craft financial hardship. The proposed technique can be a new method for forecasting groundwater resource. The analytical and prediction reports of the proposed method will assist the farmers about the accessibility of groundwater resource and lead them to plan the cultivation of right crops and prevent from economic defeat.

Internet of Things For Surgery Process Using Raspberry Pi

The development of the internet of things makes all objects interconnected, making it the next technical revolution. It has been applied extensively in various sectors, including agriculture, smart parking, and industrial places, and most importantly, in the health monitoring process.[1] To monitor or its application in surgery procedure is one of its uses in healthcare. This project proposes a system aimed to solve sudden occurrences and emergencies during the operation process. The system's objective is to minimize deaths and other possible effects of the phenomena by connecting the surgeon with an online specialist all over the world. The proposed system architecture is based on medical sensors measuring the patient's physical parameters utilizing wireless sensor networks. The sensors send the parameters to the Raspberry Pi, which converts them to digital data. The digital data is transferred over the wireless network to the server, which is then sent to the cloud environment using the internet of things. Additionally, In case of any problem, the system works by sending the surgeon a voice signal to open the system and record the message and send it with the video that was recorded by the Raspberry pi cameras through the server to all the surgeons involved in the system through the Internet of things all over the world. Then the surgeons from across the globe communicate according to his specialty of assistant surgeon to communicate with the surgeon inside the operating room through headset and microphone.

Smart City Based Autonomous Water Quality Monitoring System Using WSN

WSN can be a tech in-full development with top-notch, outstanding foreseeable future. The utilization of wireless sensor network (WSN) to get a good quality observation is consists using some range of detector nodes having a network capacity which might be set up for productive effects or to get constant monitoring function. Water is critical within our own lives because of our wellbeing insurance and in different cases such as farming, marketplace, and for the animal’s presence. Diseases linked to inadequate sanitation and water states have over 200 million cases reported causing 5–10 million deaths throughout the world. Water tracking procedures are indispensable to restrain exactly the challenge is gently linked to inadequate household allocation, wasteful usage and too little decent. Wireless sensor networks also have gained fame over the study area only because they supply a promising infrastructure for both multiple monitoring and control software. For fixing the dilemma, various drinking water caliber processes were grown previously in the last ten years. The parameters included with the drinking water quality tracking would be the PH degree, turbidity, dissolved oxygen and temperature has been quantified at the true period from the detectors that ship the info into the bottom channel or control/monitoring space. This document suggests the way the tracking platform might be set up highlighting the elements of low-cost, simple setup, and effortless maintenance and handling. Using this radio platform for tracking purpose is not only going to lower the total observation procedure expenditure in the duration of centers installation and labor price tag but can even offer versatility in the duration of location or distance. In this paper, the essential layout and execution of WSN comprising Lora (wide area network) established technological innovation is suggested. The developed system is cheap and makes it possible for customization. A few preliminary links between dimension to rate the efficiency and efficiency of the machine can also be shown.

Survey on wireless sensor networks: energy efficient optimization routing algorithms

Wireless Sensor Network is extensively utilized in numerous places, such as protection surveillance. In Wireless Sensor Network, sensing unit networks are particular arbitrarily in addition to likewise in-network relying upon the technique is used to extend the network. As sensing unit nodes make use of strength from batteries for noticing the facts in addition to forwarding data, it uses the capability for those answers. The sizable troubles in cordless networks include power optimization, protection, directing, and project type. In this paper, current procedures in escaping power utilization of Wireless Sensor Network in addition to distinctive protocols and also Methods are researched. Additionally, destiny research have a look at on strength efficiency in Wireless Sensor Network putting forward new terms as well as targets for in addition examination is mentioned. Depiction of optimizing strategies like particle swarm optimization set of rules as well as ant swarm optimization Formula is already possible for lowering the electricity loss and complements the life of sensor community but those strategies take in greater time. This paper gives surveying extraordinary different optimization techniques below the multi-objective facet that takes region in tradeoffs. Information extracting in sensing unit networks is the technique of obtaining software-enabled plans in addition to patterns with gratifying accuracy from a constant, speedy, in addition to probable non-ended flow of facts streams from sensor networks. Various boundaries in preceding optimization Algorithms and suggesting a great deal better treatment through applying Data extracting Strategies for Wireless Sensing unit Networks is carried out.

Crop Surveillance using Unmanned Aerial Vehicle for Precision Agriculture

Precision agriculture (PA) is a combination of latest technologies planned to increase the productivity and profitability by retaining the quality of the fertile land and surrounding environment. Crop monitoring in precision agriculture will be achieved by implementing innovative techniques; however the utilization of Wireless Sensor Network (WSNs) results in low power and low cost utilization arrangements thus turning into a predominant alternative. It is likewise outstanding that harvests are additionally influenced adversely by interlopers (human or animals) and by insufficient control of the production process. Crop surveillance through drone is one of the technical approaches to capture and distinguish the crop patterns, which helps in early detection of the crop damage, leads the farmers to take care for crop yield. Drone is also termed as Unmanned Aerial Vehicle (UAV). These vehicles are equipped with required electronic sensors, cameras and a flight control system to simulate the UAV, with small in size and flexible to handle and operate, These Aerial Vehicles can operate within indoor as well as at outdoor. The goal of the research is to contribute to the implementation and deployment of remote sensing technology with UAV. This paper enumerate on the applications of UAVs for crop scouting and analyzing the transmitted images using NDVI to predict the crop growth and yield.

A novel efficient clustering protocol for energy harvesting in wireless sensor networks

The utilization of wireless sensor networks (WSNs) is proliferating in our daily life. It depends on the environmental monitoring such as weather tracking, battled field, etc. However, the main challenge of WSNs is energy management. Generally, traditional nodes of the sensor network were powered by non-rechargeable batteries with limited energy capacity. The alternative solution has been discovered to resolve the limitation of the sensor battery called energy harvesting (EH). EH offers effective and an alternative solution to recharge the battery of the sensor node. It assists with the environment, and EH technique can be possible different kinds such as solar, wind, thermal and mechanical. In this paper, we propose a novel energy harvesting clustering protocol (NEHCP). The NEHCP is based on the hierarchical clustering routing algorithm, and this protocol uses solar EH. The collection of information from the sensor nodes is sent to the base station through the cluster head. The NEHCP algorithm is categorized into three sections, such as the initial phase, set-up phase and data transmission phase. Moreover, the unique feature of EH-WSNs is giving more efficient result in term of network lifetime. The simulation part of this method shows a strong ability to balance energy consumption and increases the network efficiency for the EH-WSNs.

RETRACTED ARTICLE: Cooperative spectrum sensing in wireless sensor networks using forager bee’s intelligence

Increasing utilization of wireless sensor networks Leads scarcity problems in spectrum allocation channels. The development of cognitive radio networks over wireless spectrum technology based on both licensed and unlicensed user. The maximum interference of users are mitigated to use unlicensed bandwidth. Due the high interference of bandwidth sharing enormously by secondary users (SUs). To sense the unlicensed user on over problematic condition remains the overhead problems on cognitive radio networks. In this paper, Co-operative spectrum sensing as well as spectrum allocation with Forager Bee’s Intelligence algorithm is used. The idle spectrum band in licensed band is identified and allocated to sensor nodes, which reduces the interference and collisions in WSN and avoids packet retransmission. This ensures fair energy in WSNs and Spectrum resources are utilized efficiently.

Relay Node Placement in Wireless Sensor Networks: From Theory to Practice

The increasingly wide utilization of Wireless Sensor Networks (WSNs) in industrial applications outstands the significance of the Delay Constrained Relay Node Placement (DCRNP) problem. Existing algorithms to the DCRNP problem are designed based on the ideal geometric disk wireless channel model, and no real-world deployments are performed to verify the effectiveness of these algorithms. However, the unreliable and unpredictable wireless links in WSNs may lead these algorithms to fail in practice. Therefore, we first conduct extensive real-world deployments under the guidance of existing algorithms to evaluate their performance and to gain some insights for designing practical deployment algorithms. The results exhibit that the WSNs built by existing algorithms have a favorable performance in end-to-end delay but a poor performance in reliability, which is mainly due to the lack of methods ensuring high-quality links. To this end, we first devise a Set-Covering-based Algorithm (SCA) which figures out the DCRNP problem while ensuring the quality of each link better than a given threshold. As our experiments also show that the fault-tolerant topology can significantly improve network reliability, we then design a $k$ k -Set-Covering-based Algorithm ( $k$ k SCA) to build fault-tolerant WSNs based on the methodology of SCA. Furthermore, the elaborate analysis proves that both SCA and $k$ k SCA are polynomial-time algorithms, and their approximation ratios are both O( $\ln n$ ln n ), where $n$ n is the number of sensor nodes. Finally, extensive experiments are performed under the guidance of SCA and $k$ k SCA to demonstrate the effectiveness of these two algorithms.

Stochastic Optimization of Data Access and Hybrid Transmission in Wireless Sensor Network

In recent years, the rapid advancements in Internet of Things boost the utilization of Wireless Sensor Network (WSN). Through WSN, a huge amount of various kinds of data can be acquired from different environments, which further facilitate us to harness the world we live. However, the error-prone and unpredictable natures of wireless links significantly impair the quality of data transmission and the utility of acquired data in WSN. Therefore, to solve this crucial problem, this paper focuses on data access control and hybrid transmission control of WSN. Based on the mathematical models of the two control operations, an intractable optimization problem is first formulated with numerous considerations, including data utility, energy consumption, network stability and data loss rate. Because of the complexity and intractability of the originally formulated problem, a Lyapunov function-based network optimization theory is utilized to transform and decompose it into three relatively simple subproblems. Stochastic Data Scheduling Mechanism (SDSM) is designed based on the solutions to the three subproblmes. The optimality and implementation of SDSM are also analyzed. Finally, the performance of SDSM is demonstrated through extensive evaluations.

A Review on Fault Diagnosis in Wireless Sensor Networks

With the wide utilization of wireless sensor networks(WSN), higher reliability and stability are being pursued gradually. In most cases, the communication capability for sensor network is influenced by the complex environmental conditions, the open characteristics of channels, the energy limitations of nodes, as well as network protocol design issues, ultimately leading to the high possibility of network failure. As a result, a timely and accurate fault diagnosis is of much significance for a network to ensure the stable operation and execution efficiency. This article firstly demonstrates the diagnostic process on the following three aspects, including the collection for network fault information, fault detection, and diagnosis process. In addition, the features of commonly used technologies are also analyzed and compared in order to identify their application scope respectively. Finally, this paper makes the summary for the possible development trends and future research directions of fault diagnosis.