Implementation Of Sensor Network Research Articles

Deploying Wireless Sensor Networks in Multi-Story Buildings toward Internet of Things-Based Intelligent Environments: An Empirical Study.

With the growing integration of the Internet of Things in smart buildings, it is crucial to ensure the precise implementation and operation of wireless sensor networks (WSNs). This paper aims to study the implementation aspect of WSNs in a commercial multi-story building, specifically addressing the difficulty of dealing with the variable environmental conditions on each floor. This research addresses the disparity between simulated situations and actual deployments, offering valuable insights into the potential to significantly improve the efficiency and responsiveness of building management systems. We obtain real-time sensor data to analyze and evaluate the system's performance. Our investigation is grounded in the growing importance of incorporating WSNs into buildings to create intelligent environments. We provide an in-depth analysis for scrutinizing the disparities and commonalities between the datasets obtained from real-world deployments and simulation. The results obtained show the significance of accurate simulation models for reliable data representation, providing a roadmap for further developments in the integration of WSNs into intelligent building scenarios. This research's findings highlight the potential for optimizing living and working conditions based on the real-time monitoring of critical environmental parameters. This includes insights into temperature, humidity, and light intensity, offering opportunities for enhanced comfort and efficiency in intelligent environments.

UAV-enabled software defined data collection from an adaptive WSN

AbstractUnmanned aerial vehicle (UAV)-based data gathering from wireless sensor networks is one of the recent research topics that has currently attracted research interest. One of the challenges for the UAV-aided WSN data collection efforts is to design an energy-efficient UAV/drone communication with arbitrarily dispersed ground sensors by improving the ground network structure. This paper aims to develop a technique titled UAV Fuzzy Travel Path' that supports UAV smooth path design and enables ground network topology shifting. A comprehensive UAV-based data collection model is proposed to enable dynamic orchestration/re-orchestration of wireless ground sensors to jointly improve network performance and UAV path fluidity. This provides a more flexible ground network framework that can be restructured based on network demands and UAV optimal paths, effectively allowing for a software-defined network concept. The main contribution of this work is the implementation of the software-defined wireless sensor network on the ground network that adaptably supports the movement of the UAV and enhances the communication network’s energy efficiency with a proposed latency analytical analysis via network orchestration/re-orchestration phases. The main significance of this research is in offering a flexible span for UAV path design than being fixed in one strict route for data gathering purposes. Four various simulation tools are employed for modelling and performance evaluation, namely MATLAB, CupCarbon, Contiki-Cooja and Mission Planner. The proposed software-defined ground network system demonstrates encouraging results in terms of network performance metrics including energy consumption of UAV versus ground sensor nodes energy usage, packet delivery rate, and the communication time of the ground orchestrated or/and re-orchestrated network.

Generation of Power from Footpath Using IOT

The present scenario, the requirement for energy has been increasing in a distressing rate and the availability of the energy resources are not abundant for sustainable development and the need of the hour is to establish an economical pollution free inexhaustible energy resource to compensate the increasing demands. Since, walking is the most common activity in human day to day life, whenever a person walks, he exhausts energy to the ground which goes as a waste. In order to preserve and make use of this energy we are converting it into electrical energy using piezoelectric effect. Piezoelectric effect is utilized by piezoelectric sensor producing output energy in the form of AC voltage. To produce energy in a large extent, in this model implementation of the piezoelectric sensor network along the footpath is carried out which is given to the lane of streetlights along with it the smart shoe is implemented for a small production that consists GPS tracking. In this proposed work model, GPS tracking has been added and also streetlights switching technique comparing with existing model

Wireless Sensor Network Implementation to Prevent Railway Route Accident

Wireless Sensor Network Implementation to Prevent Railway Route Accident

АРХІТЕКТУРА ТА МОДЕЛІ НАДІЙНОСТІ ГІБРИДНИХ СЕНСОРНИХ МЕРЕЖ СИСТЕМ ЕКОЛОГІЧНОГО ТА АВАРІЙНОГО МОНІТОРИНГУ

The authors study the aspects of developing and analyzing the hybrid sensor networks’ operability as subsystems of environmental and emergency monitoring systems for critical infrastructure. The proposed architecture of such a system is based on the technology of edge computing (EC) and combines stationary and mobile components, the first of which is implemented by a ground sensor network (GSN), and the second by a swarm of unmanned aerial vehicles that form a flying EC network. The data collection algorithms, scaling problems, and optimization of the operation of the GSN and monitoring systems in general are analyzed. The reliability models of the GSN in the conditions of failure of one and groups of sensors are developed and investigated. Analytical dependencies of reliability indicators on different sizes of sensor failure clusters and their intensity are obtained. Recommendations for the design and implementation of hybrid sensor networks are given. Keywords: hybrid sensor networks, edge computing, reliability models, multiple failures, environmental monitoring systems, emergency monitoring systems.

Sink Node Placement and Partial Connectivity in Wireless Sensor Networks.

This research delves into the aspects of communication and connectivity problems within random Wireless Sensor Networks (WSNs). It takes into account the distinctive role of the sink node, its placement, and application-specific requirements for effective communication while conserving valuable network resources. Through mathematical modeling, theoretical analysis, and simulation evaluations, we derive, compare, and contrast the probabilities of partial and full connectivity within a random WSN, factoring in network parameters and the maximum allowable hop distance/count hmax. hmax captures the diverse range of delay-sensitive requirements encountered in practical scenarios. Our research underscores the significant impact of the sink node and its placement on network connectivity and the sensor connection rate. The results exemplify a noteworthy decline in the sensor connection rate, dropping from 98.8% to 72.5%, upon relocating the sink node from the network center to the periphery. Moreover, as compared with full connectivity, partial connectivity and the sensor connection rate are more suitable metrics for assessing the communication capability of random WSNs. The results illustrate that 1.367 times more energy is required to connect less than 4% of the remote sensors, based on the examined network settings. Additionally, to increase the sensor connection rate slightly from 96% to 100%, an additional 538% more energy is required in multipath fading based on the widely adopted energy consumption model. This research and its outcomes contribute to establishing appropriate performance metrics and determining critical network parameters for the practical design and implementation of real-world wireless sensor networks.

Wearable Wireless Sensor Network for Mitigating COVID-19 Transmission Through Physical Distancing

The global community is currently facing a critical situation with the widespread transmission of the Covid-19 virus. The rapid increase in Covid-19 cases has necessitated immediate action and treatment. As the World Health Organization (WHO) recommended, maintaining a minimum distance of one meter between individuals is an effective preventive measure to avoid transmission through respiratory droplets. To address this issue, this paper introduces a cost-effective design and implementation of a wearable wireless sensor network using the ESP32 microcontroller and Bluetooth Low-Energy (BLE) technology that promotes physical distancing and contact tracing to mitigate the spread of COVID-19. In this research, we have determined that the safe distance between individuals is 1.5 meters. Proximity testing has indicated that an RSSI value of -62 dBm corresponds to a distance below 1.5 meters. Hence, we set -62 dBm as the distance threshold between wearable devices to ensure safe physical distancing. These wearable wireless sensor network devices are intended to assist individuals in maintaining a safe distance from others, thereby reducing the risk of COVID-19 transmission.

Energy Efficient Data Aggregation Approach for Sensor Network using Trust Mechanism

A wireless sensor network consists of numerous sensor nodes which are capable of entering and departing from the network according to their wish. The implementation of sensor networks is done at far places and they are small-sized. Thus, energy consumption becomes the main issue of WSN. Due to the limited energy of sensor nodes, the data that is collected from the intended environment is sent directly to the main station. The sink node receives the data that several sensor nodes send. The decision-making process is implemented by identifying and removing similarities between the data from various sensor nodes. In addition, the sink makes the deployment of obtained data locally as well as transmits these data to the networks which are executed far away. The existing research work employs CTNR, an energy-efficient protocol that is capable of enhancing the duration of WSN. The CTNR protocol consists of two-level hierarchies for mitigating the energy utilized in WSN. This protocol assists in choosing the CHs (cluster heads) on the basis of distance and energy. This work will focus on enhancing the CTNR routing algorithm so that the life span of the network can be prolonged.

DYNAMIC PRESSURE MONITORING USING A WIRELESS SENSOR NETWORK

This study introduces the build out and implementation of a wireless sensor network that was used to monitor dynamic pressure of water flowing inside a pipe against leak. At 5 chosen points along a prototype water pipeline, pressure sensors (HK1100C) were used to collect pressure data and its voltage data equivalent. Five locally designed and constructed field sensor nodes made up of pressure sensors, Ardiuno boards containing an 8-bit ATmega328P microcontrollers, GSM SIM800L modules, and power sources were used to process and analyze the pressure data such that when the pressure data falls below 9psi, 9.5psi, 10psi, 10.5psi, and 11psi respectively at the 5 chosen points, the information is processed by the Ardiuno boards containing an 8-bit Atmega328P microcontrollers and then passed on to the GSM SIM800L modules of respective field sensor nodes which then transmit these information as radio waves to the master sensor node of the network that has an LCD JHD162 module and a buzzer.. The received radio waves were converted back into electrical signals by the transceiver contained in the GSM SIM800L module of the master sensor node and used to power the LCD and buzzer to indicate ‘low pressure’ and sound an alarm simultaneously. The location of the pressure drop is identified and the cause rectified by trained personnel. SIM cards of chosen GSM networks were inserted into the various GSM SIM800L modules contained in the sensor nodes (fields and master nodes) for communication. Also, an experiential evaluation of the relationship between leaks and pressure variations was carried out at one of the chosen 5 points along the prototype water pipeline.

Optimization of PZT Wafers’ placement with enhanced level of robustness using multiple interacting networks

Continuous monitoring and in particular structural health monitoring (SHM) of structures is used, nowadays, by asset managers to ensure a high level of safety and extend the lifetime of their assets. One of the main bottlenecks faced in the development of an SHM system is the design and implementation of sensor networks. This includes selecting the sensor type and optimizing the number and positions of sensors. This study proposes a novel approach to account for the potential loss in sensing elements within the network, by having multiple independent networks but at the same time interacting for enhanced performance. The developed model considers the PZT locations as continuous variables where any point on the surface can be a sensor location. The model can handle complex structures and customize to different wave characteristics and coverage levels.The objective function in the developed model aims at maximizing a weighted sum of two dependent terms: the coverage which is the percentage of covered control points within the network, and the robustness which is the average number of networks covering each covered control point. The proposed model was solved using a genetic algorithm and was tested on several geometries. To mimic a faulty sensor within the network, a complete network was removed in each case, and it was found that the coverage was not impacted. The effect of the partitioning of large sections on the performance of the optimizer was explored.Experimental validations were carried out to evaluate the model's accuracy in damage localization within the optimized sensor networks and to emphasize the importance of each of the coverage and robustness. The results demonstrated the proficiency of the model developed in distributing the piezoelectric ceramics (PZTs) on the tested specimens, and its ability to detect damages more precisely in more robust configurations where multiple networks participate in covering wide regions.

An integrated system for the acoustic monitoring of goat farms

Effective precision livestock farming requires the availability of reliable and up-to-date data characterizing the animals and environment of interest. This work presents the design, architecture, and implementation of a wireless acoustic sensor network for monitoring goat farms on a 24/7 basis. In addition, we define a hierarchical organization of the involved sound classes exhaustively covering every aspect of the encountered goat vocalizations. Moreover, we developed an annotation tool tailored to the specifics of the problem at hand, i.e. a big, real-world data environment, able to meaningfully assist the annotation of goat vocalizations via a suitable sound classification module. On top of that, a mobile phone application was developed facilitating authorized users to remotely access information describing the situation on the farm site. Importantly, such a non-invasive monitoring framework was installed in 4 different sites located in Northern Italy while taking into account their diverse characteristics.

Research on the design of green and low-carbon food packaging based on artificial intelligence technology

<p>An economic system focused on low energy usage, low pollution, and low emission is known as a "low-carbon economy". The concept of environmentally friendly and low-carbon food packaging architecture directs practice growth and reform in accordance with the customer's green psychology. As the primary benchmark for packaging concerned with designing practices, it uses the green conceptual design of contemporary eco-environmental preservation and other meaningful reforms. It is significant need to mix people's developed green psychology with this issue in order to discover a solution for green packaging design. The design and use of eco-friendly and low-carbon food packaging is covered in this research. With the implementation of wireless sensor network (WSN) and Artificial Intelligence (AI) technique, it accomplishes the fusion of market and ecologically responsible design, enhances production effectiveness and product usage. The confidence weight information choice technique is used to determine the type of smart energy-saving packaging, and the fundamental element is that the energy usage vector is formed by an Artificial Neural Network (ANN). Packaging makers must reevaluate how design and the environment interact, eliminate packaging design pollutants, make environmental protection their top concern, and develop a design idea that complies with ecological ethics for the long-term profit of human survival. Environment, politics, economy, and social factors all play a role in how the food system functions and are influenced by them. Compared to traditional techniques for monitoring the environment We use wireless sensor networks to keep an eye on the agricultural environment because they have three key benefits: (1) There is no need to lay wire; (2) the system is only implemented once; (3) the nodes are dense; (4) collected data has good precision; and (5) sensor nodes with a specific calculation and storage capacity, enabling collaboration among nodes, are perfect for unsupervised monitoring system. The incorporation and handling of product packaging data is made possible by smart packaging technology, which is essential in the creation of low-carbon food packaging and helps</p>

SOLARIA-SensOr-driven resiLient and adaptive monitoRIng of farm Animals

Sensor-enabled big data and artificial intelligence platforms have the potential to address global socio-economic trends related to the livestock production sector through advances in the digitization of precision livestock farming. The increased interest in animal welfare, the likely reduction in the number of animals in relation to population growth in the coming decade and the growing demand for animal proteins pose an acute challenge to prioritizing animal welfare on the one hand, while maximizing the efficiency of production systems on the other. Current digital approaches do not meet these challenges due to a lack of efficient and lack of real-time non-invasive precision measurement technologies that can detect and monitor animal diseases and identify resilience in animals. In this opinion review paper, I offer a critical view of the potential of wearable sensor technologies as a unique and necessary contribution to the global market for farm animal health monitoring. To stimulate the sustainable, digital and resilient recovery of the agricultural and livestock industrial sector, there is an urgent need for testing and developing new ideas and products such as wearable sensors. By validating and demonstrating a fully functional wearable sensor prototype within an operational environment on the livestock farm that includes a miniaturized animal-borne biosensor and an artificial intelligence (AI)-based data acquisition and processing platform, the current needs, which have not yet been met, can be fulfilled. The expected quantifiable results from wearable biosensors will demonstrate that the digitization technology can perform acceptably within the performance parameters specified by the agricultural sector and under operational conditions, to measurably improve livestock productivity and health. The successful implementation of the digital wearable sensor networks would provide actionable real-time information on animal health status and can be deployed directly on the livestock farm, which will strengthen the green and digital recovery of the economy due to its significant and innovative potential.

Design and Development of Solar Powered Automatic Irrigation System for Modernization of Agriculture

The aim of research is to reduce the utilization of water by irrigating the agricultural fields that have low moisture level through the implementation of Wireless Sensor Network (WSN). The ARM-based irrigation solution consists of a Solar Tracking System, Wireless Information Unit (WIU), WSN and Remote Access. The Solar Tracking System utilizes maximum solar energy by using Light Dependent Resistor(LDR) to track the sun. The electric energy produced is stored in the battery which powers the ARM processor. Wireless Information Unit will collect the sensor information from Wireless Sensor Network through the use of Wi-Fi. The system monitors soil-moisture and controls the flow of water using a solenoid valve depending upon the set threshold. In the tank, Ultra Sonic sensor identifies the water level controlled by the WIU. An Android application helps the farmer to monitor the water flow and soil moisture remotely. The proposed water management methodologies for agriculture optimizes the water usage and such practices maintain the crop health, keep yield intact, and avoids human intervention. In this proposed system, soil moisture is maintained appropriately to ensure that a good harvest is obtained which in turn preserves different types of nutrients.

Ultra Wide Band communication for condition-based monitoring, a bridge between edge and cloud computing

Ultra Wide Band (UWB) wireless communications offer a radically different approach to wireless communication compared to conventional narrow band systems in an industrial context. A lot of industrial applications do not require real-time acquisition and uses low data rates, but some scenarios, such as the condition monitoring systems and the control processes require higher data rates (i.e. tens of kHz). General purpose wireless solutions do not compliant industrial standards. This paper discusses the potential of UWB technology for realizing use cases in industry 4.0 and shows the implementation of an UWB sensor network for machine vibration monitoring that is able to acquire and transmit (6.8Mbit/s data rate) accelerometric measures sampled up to 32KHz with a maximum Packet Loss Rate (PLR) of 2.44%. It also shows as UWB could be a valid instrument to connect cloud computing and edge computing even for real time extraction of diagnostic and prognostic features from high-frequency signals. Different experiments have been performed in an industrial and laboratory environment to evaluate the performance of UWB radio for communication in a wireless sensor network.

Wireless Sensor Network Based Monitoring System: Implementation, Constraints, and Solution

Wireless Sensor Network (WSN) is a collection of sensors communicating at close range by forming a wireless-based network (wireless). Since 2015 research related to the use of WSN in various health, agriculture, security industry, and other fields has continued to grow. One interesting research case is the use of WSN for the monitoring process by collecting data using sensors placed and distributed in locations based on a wireless system. Sensors with low power, multifunction, supported by a combination of wireless network, microcontroller, memory, operating system, radio communication, and energy source in the form of an integrated battery enable a monitoring process of the monitoring area to run properly. The implementation of the wireless sensor network includes five main parts, namely sender, receiver, wireless transmission media, data/information, network architecture/configuration, and network management. Network management itself includes network configuration management, network performance management, network failure management, network security management, and network financing management. The main obstacles in implementing a wireless sensor network include three things: an effective and efficient data sending/receiving process, limited and easily depleted sensor energy/power, network security, and data security that is vulnerable to eavesdropping and destruction. This paper presents a taxonomy related to the constraints in implementing Wireless Sensor Networks. This paper also presents solutions from existing studies related to the constraints of implementing the WSN. Furthermore, from the results of the taxonomy mapping of these constraints, new gaps were identified related to developing existing research to produce better solutions.

Implementation of Wireless Sensor Network (WSN) for Earthquake Detection

The current earthquake monitoring system uses a seismometer that can capture seismic vibrations very well but is expensive, heavy, and difficult to launch. Therefore, earthquake monitoring stations can only be launched in a few places in small numbers. This study aims to implement a Wireless Sensor Network (WSN) system for earthquake monitoring. The WSN system has advantages in cost, size, and ease of launch, so it is very appropriate to be used for this purpose. An earthquake detection sensor system has been designed in this study using a vibration sensor and a piezoelectric sensor. When an earthquake occurs, the resulting shock will trigger the vibration sensor and activate the sensor node. The shock data is then captured by the piezo sensor and processed by the microcontroller using Fast Fourier Transform (FFT) to determine the frequency value of the shock. The data is then sent to a gateway via a sensor network and uploaded to the Cayenne monitoring website. Operators can then view the data on the website. Three sensor nodes are implemented in this study. The test is done by placing those sensor nodes together in random positions. A shock is then given to the three sensor nodes, and the resulting data is then observed. The results show that the three sensors can detect, retrieve, process, and send shock data to the Cayenne monitoring website.

Energy-Efficient Routing Protocols for Wireless Sensor Networks: Architectures, Strategies, and Performance

Recent developments in low-power communication and signal processing technologies have led to the extensive implementation of wireless sensor networks (WSNs). In a WSN environment, cluster formation and cluster head (CH) selection consume significant energy. Typically, the CH is chosen probabilistically, without considering the real-time factors such as the remaining energy, number of clusters, distance, location, and number of functional nodes to boost network lifetime. Based on the real-time issues, different strategies must be incorporated to design a generic protocol suited for applications such as environment and health monitoring, animal tracking, and home automation. Elementary protocols such as LEACH and centralized-LEACH are well proven, but gradually limitations evolved due to increasing desire and need for proper modification over time. Since the selection of CHs has always been an important criterion for clustered networks, this paper overviews the modifications in the threshold value of CH selection in the network. With the evolution of bio-inspired algorithms, the CH selection has also been enhanced considering the behavior of the network. This paper includes a brief description of LEACH-based and bio-inspired protocols, their pros and cons, assumptions, and the criteria of CH selection. Finally, the performance factors such as longevity, scalability, and packet delivery ratio of various protocols are compared and discussed.

A Survey on Monitoring Quality Assessment for Wireless Visual Sensor Networks

Wireless visual sensor networks have been adopted in different contexts to provide visual information in a more flexible and distributed way, supporting the development of different innovative applications. Although visual data may be central for a considerable set of applications in areas such as Smart Cities, Industry 4.0, and Vehicular Networks, the actual visual data quality may be not easily determined since it may be associated with many factors that depend on the characteristics of the considered application scenario. This entails several aspects from the quality of captured images (sharpness, definition, resolution) to the characteristics of the networks such as employed hardware, power consumption, and networking efficiency. In order to better support quality analysis and performance comparisons among different wireless visual sensor networks, which could be valuable in many monitoring scenarios, this article surveys this area with special concern on assessment mechanisms and quality metrics. In this context, a novel classification approach is proposed to better categorize the diverse applicable metrics for quality assessment of visual monitoring procedures. Hence, this article yields a practical guide for analyzing different visual sensor network implementations, allowing fairer evaluations and comparisons among a variety of research works. Critical analysis are also performed regarding the relevance and usage of the proposed categories and identified quality metrics. Finally, promising open issues and research directions are discussed in order to guide new developments in this research field.

Design and implementation of wireless sensor network for environmental monitoring

Wireless Sensor Networks (WSN) are being developed in the agriculture and weather station sectors to monitor and manage a number of objects. Sensor network hardware platforms are low-power embedded systems featuring a variety of sensors, such as on-board sensors and analogue I/O ports for adding sensors. The design of genuine environmental monitoring and communication systems is greatly aided by the creation of a WSN. A WSN is a collection of sensors that are geographically spread and specialized for monitoring and recording environmental variables and storing the findings in a central location. Limited power consumption as sensor nodes works on batteries, Nodes are mobile opposed to conventional wires, Usage in harsh environment, Nodes can be deployed in any fashion over an area, Easy to use and multi-layer design operation these are the main characteristics of WSN. Limits imposed on the energy storage device by their applications and deployment settings are less relevant to WSN environment-monitoring applications than controlling power consumption and optimizing data transmission. A WSN is used to record real-time traffic and environmental data in order to develop descriptive and predictive models for determining the optimum routes to reduce traffic congestion and, as a result, urban pollution. C