Tareq Alhmiedat
University of Tabuk, Information Technology, Department Member
- Tracking mobile targets indoors, Robotic Design and Applications, WSN design and applications, Computer Science, Neural Networks, Zigbee Based Mobile Tracking System, and 19 moreDesign, Usability, Importance, Educational Educational, Education, History, Philosophy, Business, Sociology, Communication, Machine Learning, Cloud Computing, Wireless Sensor Networks, Android, Mobile Technology, Security, Computer Security, Mobile Computing, and Networkingedit
In recent years, advances in signal processing have led to small, low power, inexpensive Wireless Sensor Network (WSN). Target localisation and tracking problems in WSNs have received considerable attention recently, driven by the... more
In recent years, advances in signal processing have led to small, low power, inexpensive Wireless Sensor Network (WSN). Target localisation and tracking problems in WSNs have received considerable attention recently, driven by the necessity to achieve higher localisation accuracy, lower cost, and the smallest form factor. This book includes five studies. The first study leads to the design and implementation of a triangulation-based localisation approach using RSS technique for indoor tracking applications. The second study concentrates on investigating a fingerprinting localisation method for indoor tracking applications. The third study focuses on designing and implementing a decentralised tracking approach for tracking multiple mobile targets with low resource requirements. The fourth study focuses on developing and designing a practical ZigBee-based tracking approach. The fifth study outlines designing and implementing an energy-efficient approach for tracking applications.
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Asthma is a chronic respiratory disease that impairs breathing. Management of asthma presents a significant challenge due to its inherent variability; that is, its symptoms can substantially differ among individuals, thereby complicating... more
Asthma is a chronic respiratory disease that impairs breathing. Management of asthma presents a significant challenge due to its inherent variability; that is, its symptoms can substantially differ among individuals, thereby complicating the prediction and management of exacerbations. Furthermore, individuals with asthma often have unique triggers that precipitate symptoms or attacks. The identification of these triggers can often prove to be a challenging, and at times, an impractical attempt. To address this, our research proposes a practical, personalized alert system, predicated on individual lung function tests conducted under varying environmental conditions classified by air-quality sensors. To validate this concept, we conducted an observational pilot study involving healthy individuals. We recruited twelve healthy participants and monitored their responses across a broad spectrum of environments, characterized by varying air quality, temperature, and humidity conditions. The lung function for each participant, assessed using peak expiratory flow (PEF) values, was recorded in each of these environments. Our results highlighted substantial variability in pulmonary responses to different environments. Utilizing these insights, we proposed a personalized alarm system that provides real-time air-quality monitoring and issues alerts when environmental conditions may potentially become unfavorable. We also explored the feasibility of employing basic machine learning techniques to predict PEF values in the aforementioned environmental conditions. This proposed system has the potential to empower individuals in actively safeguarding their respiratory health and mitigating discomfort caused by environmental conditions, especially in cases of asthma patients. By enabling timely and personalized interventions, the system aims to provide individuals with the necessary tools to minimize exposure to asthma’s possible triggers.
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Asthma is a chronic respiratory disease that impairs breathing. Management of asthma presents a significant challenge due to its inherent variability; that is, its symptoms can substantially differ among individuals, thereby complicating... more
Asthma is a chronic respiratory disease that impairs breathing. Management of asthma presents a significant challenge due to its inherent variability; that is, its symptoms can substantially differ among individuals, thereby complicating the prediction and management of exacerbations. Furthermore, individuals with asthma often have unique triggers that precipitate symptoms or attacks. The identification of these triggers can often prove to be a challenging, and at times, an impractical attempt. To address this, our research proposes a practical, personalized alert system, predicated on individual lung function tests conducted under varying environmental conditions classified by air-quality sensors. To validate this concept, we conducted an observational pilot study involving healthy individuals. We recruited twelve healthy participants and monitored their responses across a broad spectrum of environments, characterized by varying air quality, temperature, and humidity conditions. The lung function for each participant, assessed using peak expiratory flow (PEF) values, was recorded in each of these environments. Our results highlighted substantial variability in pulmonary responses to different environments. Utilizing these insights, we proposed a personalized alarm system that provides real-time air-quality monitoring and issues alerts when environmental conditions may potentially become unfavorable. We also explored the feasibility of employing basic machine learning techniques to predict PEF values in the aforementioned environmental conditions. This proposed system has the potential to empower individuals in actively safeguarding their respiratory health and mitigating discomfort caused by environmental conditions, especially in cases of asthma patients. By enabling timely and personalized interventions, the system aims to provide individuals with the necessary tools to minimize exposure to asthma’s possible triggers.
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Dynamic Source Routing (DSR) is an efficient on-demand routing protocol for mobile ad-hoc networks (MANET). It depends on two main procedures: Route Discovery and Route Maintenance. Route discovery is the procedure used at the source of... more
Dynamic Source Routing (DSR) is an efficient on-demand routing protocol for mobile ad-hoc networks (MANET). It depends on two main procedures: Route Discovery and Route Maintenance. Route discovery is the procedure used at the source of the packets to discover a route to the destination. Route Maintenance is the procedure that discovers link failures and repairs them. Route caching is the sub procedure serviceable to avoid the demand for discovering a route or to reduce route discovery delay before every data packet is sent. The goal of this paper is to evaluate the performance of DSR. Different performance expressions are investigated including, delivery ratio, end to-end delay, and throughput, depending on different cache sizes and different speeds. All of that as a study to develop a new caching strategy as a future work.
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Modern wheelchairs, with advanced and robotic technologies, could not reach the life of millions of disabled people due to their high costs, technical limitations, and safety issues. This paper proposes a gesture-controlled smart... more
Modern wheelchairs, with advanced and robotic technologies, could not reach the life of millions of disabled people due to their high costs, technical limitations, and safety issues. This paper proposes a gesture-controlled smart wheelchair system with an IoT-enabled fall detection mechanism to overcome these problems. It can recognize gestures using Convolutional Neural Network (CNN) model along with computer vision algorithms and can control the wheelchair automatically by utilizing these gestures. It maintains the safety of the users by performing fall detection with IoT-based emergency messaging systems. The development cost of the overall system is cheap and is lesser than USD 300. Hence, it is expected that the proposed smart wheelchair should be affordable, safe, and helpful to physically disordered people in their independent mobility.
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With the massive outbreak of coronavirus (COVID-19) disease, the demand for automatic and quick detection of COVID-19 has become a crucial challenge for scientists around the world. Many researchers are working on finding an automated and... more
With the massive outbreak of coronavirus (COVID-19) disease, the demand for automatic and quick detection of COVID-19 has become a crucial challenge for scientists around the world. Many researchers are working on finding an automated and effective system for detecting COVID-19. They have found that computed tomography (CT-scan) and X-ray images of COVID-19 infected patients can provide more accurate and faster results. In this paper, an automated system is proposed named as COV-CTX which can detect COVID-19 from CT-scan and X-ray images. The system consists of three different CNN models: VGG16, VGG16- InceptionV3-ResNet50, and Francois CNN. The models are trained with CT-scan and X-ray images individually to classify COVID-19 and non-COVID patients. Finally, the results of the models are combined to develop a voting ensemble of classifiers to ensure more accurate and precise results. The three models are trained and validated with 9412 CT-scan images (4756 numbers of COVID positive...
Robot navigation in indoor environments has become an essential task for several applications, including situations in which a mobile robot needs to travel independently to a certain location safely and using the shortest path possible.... more
Robot navigation in indoor environments has become an essential task for several applications, including situations in which a mobile robot needs to travel independently to a certain location safely and using the shortest path possible. However, indoor robot navigation faces challenges, such as obstacles and a dynamic environment. This paper addresses the problem of social robot navigation in dynamic indoor environments, through developing an efficient SLAM-based localization and navigation system for service robots using the Pepper robot platform. In addition, this paper discusses the issue of developing this system in a way that allows the robot to navigate freely in complex indoor environments and efficiently interact with humans. The developed Pepper-based navigation system has been validated using the Robot Operating System (ROS), an efficient robot platform architecture, in two different indoor environments. The obtained results show an efficient navigation system with an aver...
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Social robots have the potential to revolutionize the way we interact with technology, providing a wide range of services and applications in various domains, such as healthcare, education, and entertainment. However, most existing social... more
Social robots have the potential to revolutionize the way we interact with technology, providing a wide range of services and applications in various domains, such as healthcare, education, and entertainment. However, most existing social robotics platforms are operated based on embedded computers, which limits the robot’s capabilities to access advanced AI-based platforms available online and which are required for sophisticated physical human–robot interactions (such as Google Cloud AI, Microsoft Azure Machine Learning, IBM Watson, ChatGPT, etc.). In this research project, we introduce a cloud-based framework that utilizes the benefits of cloud computing and clustering to enhance the capabilities of social robots and overcome the limitations of current embedded platforms. The proposed framework was tested in different robots to assess the general feasibility of the solution, including a customized robot, “BuSaif”, and commercialized robots, “Husky”, “NAO”, and “Pepper”. Our findin...
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The area of localization in wireless sensor networks (WSNs) has received considerable attention recently, driven by the need to develop an accurate localization system with the minimum cost and energy consumption possible. On the other... more
The area of localization in wireless sensor networks (WSNs) has received considerable attention recently, driven by the need to develop an accurate localization system with the minimum cost and energy consumption possible. On the other hand, machine learning (ML) algorithms have been employed widely in several WSN-based applications (data gathering, clustering, energy-harvesting, and node localization) and showed an enhancement in the obtained results. In this paper, an efficient WSN-based fingerprinting localization system for indoor environments based on a low-cost sensor architecture, through establishing an indoor fingerprinting dataset and adopting four tailored ML models, is presented. The proposed system was validated by real experiments conducted in complex indoor environments with several obstacles and walls and achieves an efficient localization accuracy with an average of 1.4 m. In addition, through real experiments, we analyze and discuss the impact of reference point de...
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Usually, wireless sensor networks (WSNs) are installed in large areas to monitor various physical conditions of the environment and forward the collected sensed data to a base station (central node), for instance: gas monitoring,... more
Usually, wireless sensor networks (WSNs) are installed in large areas to monitor various physical conditions of the environment and forward the collected sensed data to a base station (central node), for instance: gas monitoring, intrusion detection, tracking objects, etc. However, sensor nodes are usually deployed unattended and battery-powered with no external power source. Therefore, WSNs face the challenge of limited energy source available onboard, where packet transmission and sensing functions are the most power consumption factors in WSN. Therefore, to overcome the energy depletion in sensor nodes, it is important to study the energy management issue in WSN. In this chapter, the significance of energy management issue is discussed first, and then the possible energy management strategies for WSN are presented and illustrated.
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There is increasing utilization of photovoltaic (PV) grid-connected systems in modern power networks. Currently, PV grid-connected systems utilize transformerless inverters that have the advantages of being low cost, low weight, a small... more
There is increasing utilization of photovoltaic (PV) grid-connected systems in modern power networks. Currently, PV grid-connected systems utilize transformerless inverters that have the advantages of being low cost, low weight, a small size, and highly efficient. Unfortunately, these inverters have an earth leakage current problem due to the absence of galvanic isolation. This phenomenon represents safety and electrical problems for those systems. Recently, the H8 transformerless inverter was introduced to eliminate the earth leakage current. The present study proposes improving the performance of an H8 transformerless inverter using model predictive control (MPC). The inverter was supplied by PV energy and attached to the grid through an LCL filter. During system modeling, the grid weakness was identified. The discrete model of the overall system, including the PV panel, the boost converter, the H8 transformerless inverter, and the controllers, was derived. Then, the introduced H8...
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Using mobile sinks to collect information in wireless sensor networks is an interesting area of research. As a result, a variety of mobility models were proposed by researchers over the years where each mobility model has its own... more
Using mobile sinks to collect information in wireless sensor networks is an interesting area of research. As a result, a variety of mobility models were proposed by researchers over the years where each mobility model has its own properties that may affect the performance of the network in a way that differs from other models entitled with different properties. In this paper we provide a survey of mobility models that can be used in wireless sensor networks since it is important to provide a classification of the available models. Therefore, several mobility models were reviewed in the proposed work. These models were classified into two main categories namely homogenous and heterogeneous mobility. The goal of the work proposed in this paper is to provide researchers with a clear idea about the available mobility models and their properties. Additionally, we aim to provide researchers with guidelines to help them choose mobility models properly.
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paper evaluates the performance of the OLSR pro-active protocol with and without backup routes under varying node densities and with different speed movements in the network. Additionally, this paper assists in ascertaining the effect of... more
paper evaluates the performance of the OLSR pro-active protocol with and without backup routes under varying node densities and with different speed movements in the network. Additionally, this paper assists in ascertaining the effect of varying node densities on the connectivity's life between mobile nodes in the network. Hence, it showed the affect of a local recovery mechanism resulted in achieving a significant improvement in network performance by seeking a long life backup path between source and destination for low/high density nodes. Real time applications are required to be supported by mobile ad hoc networks. This is because of the free movement for the mobile nodes from one area to another without any notification via frequent paths. The real time applications traffics are considered a sensitive application, and it is the most affected by failure through the occurrence of delay and loss of packets. It is, therefore, not suitable for use by players. In mobile ad hoc ne...
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Autonomous robots are designed to discover and interpret their surroundings and orient themselves around obstacles to reach the destination point from an initial point. Robot autonomous navigation is a requirement for maze-solving... more
Autonomous robots are designed to discover and interpret their surroundings and orient themselves around obstacles to reach the destination point from an initial point. Robot autonomous navigation is a requirement for maze-solving systems, where the solver robot is required to navigate the maze area to get its desire destination location using the fastest route possible. In this paper, a new, modified wall-follower system for a maze-solving robot was proposed that overcame the infinite loop-back issue in the traditional wall-follower approaches. We also investigated and analyzed the performance of three different maze-solving algorithms and compared them with the proposed, modified wall-follower robotic system by conducting several real experiments to validate the efficiency of the developed wall-follower robotic system.
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Dynamic Source Routing (DSR) is an efficient on-demand routing protocol for mobile ad-hoc networks (MANET). It depends on two main procedures: Route Discovery and Route Maintenance. Route discovery is the procedure used at the source of... more
Dynamic Source Routing (DSR) is an efficient on-demand routing protocol for mobile ad-hoc networks (MANET). It depends on two main procedures: Route Discovery and Route Maintenance. Route discovery is the procedure used at the source of the packets to discover a route to the destination. Route Maintenance is the procedure that discovers link failures and repairs them. Route caching is the sub procedure serviceable to avoid the demand for discovering a route or to reduce route discovery delay before every data packet is sent. The goal of this paper is to evaluate the performance of DSR. Different performance expressions are investigated including, delivery ratio, end to-end delay, and throughput, depending on different cache sizes and different speeds. All of that as a study to develop a new caching strategy as a future work.
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Mobile technology is becoming more popular around the world. The importance of such technology relates to its capability of allowing the user of performing many different daily basis tasks. Despite the progress made in the mobile... more
Mobile technology is becoming more popular around the world. The importance of such technology relates to its capability of allowing the user of performing many different daily basis tasks. Despite the progress made in the mobile application field, there are still some boundaries and limitations in using it. Some of these difficulties are connected directly to the Culture. Other difficulties are related to the experience in using such technology. This research aims to find out the main restrictions and obstacles which limit the use of mobile handsets as an Islamic smart Hajj and Umra Application. The research aim extends to studying the effect of cultural issues on peoples use of the internet on a mobile phone. The research reported here is based on participants from the Hashemite Kingdome of Jordan.
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The problem of long bended routes in Kingdom of Saudi Arabia (KSA) is one of the annoying problems that harvest a big number of vitalities annually. The problem relays under the fact that these long bended route are in shortage for... more
The problem of long bended routes in Kingdom of Saudi Arabia (KSA) is one of the annoying problems that harvest a big number of vitalities annually. The problem relays under the fact that these long bended route are in shortage for lighting because of its extremely high cost. Therefore, in this paper, a system will be proposed as a smart alerting system based on ZigBee sensor network. The proposed system targets the roads with weak lights at night time in order to reduce the number of accidents which may occur on such dangerous roads. A number of real experiments were conducted using ZigBee sensor nodes in order to test the efficiency and reliability of the proposed system. Through real experiments, it was demonstrated that the proposed system offers reasonable response time, and achieves low power consumption.
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ABSTRACT
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Research Interests: Computer Science, Distributed Computing, Wireless Sensor Networks, Localization, Energy Consumption, and 9 moreComputer Network, Computer Software, Power Consumption, Wireless Sensor and Mobile Adhoc Networks, Tracking Vehicles in Real Time, ZigBee, Decentralized Communication, Wireless Sensor Network, and arXiv
Forest fires are a serious ecological concern, and smoke is an early warning indicator. Early smoke images barely capture a tiny portion of the total smoke. Because of the irregular nature of smoke’s dispersion and the dynamic nature of... more
Forest fires are a serious ecological concern, and smoke is an early warning indicator. Early smoke images barely capture a tiny portion of the total smoke. Because of the irregular nature of smoke’s dispersion and the dynamic nature of the surrounding environment, smoke identification is complicated by minor pixel-based traits. This study presents a new framework that decreases the sensitivity of various YOLO detection models. Additionally, we compare the detection performance and speed of different YOLO models such as YOLOv3, YOLOv5, and YOLOv7 with prior ones such as Fast R-CNN and Faster R-CNN. Moreover, we follow the use of a collected dataset that describes three distinct detection areas, namely close, medium, and far distance, to identify the detection model’s ability to recognize smoke targets correctly. Our model outperforms the gold-standard detection method on a multi-oriented dataset for detecting forest smoke by an mAP accuracy of 96.8% at an IoU of 0.5 using YOLOv5x. A...
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In recent years, advances in signal processing have led to small, low power, inexpensive Wireless Sensor Network (WSN). The signal processing in WSN is different from the traditional wireless networks in two critical aspects: firstly, the... more
In recent years, advances in signal processing have led to small, low power, inexpensive Wireless Sensor Network (WSN). The signal processing in WSN is different from the traditional wireless networks in two critical aspects: firstly, the signal processing in WSN is performed in a fully distributed manner, unlike in traditional wireless networks; secondly, due to the limited computation capabilities of sensor networks, it is essential to develop an energy and bandwidth efficient signal processing algorithms. Target localisation and ...
This paper presents a low-cost system architecture that has been proposed for automatically monitoring air quality indoors and continuously in real-time. The designed system is in pilot phase where 4 sensor nodes are deployed in indoor... more
This paper presents a low-cost system architecture that has been proposed for automatically monitoring air quality indoors and continuously in real-time. The designed system is in pilot phase where 4 sensor nodes are deployed in indoor environment, and data over 4 weeks has been collected and performance analysis and assessment are performed. Environmental data from sensor nodes are sent through ZigBee communication protocol. The proposed system is low in cost, and achieves low power consumption. Hardware and network architecture are presented in addition to real-world deployment.
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People with visual impairment face enormous difficulties in terms of their mobility as they do not have enough information about their location and orientation with respect to traffic and obstacles on their route. Visually impaired people... more
People with visual impairment face enormous difficulties in terms of their mobility as they do not have enough information about their location and orientation with respect to traffic and obstacles on their route. Visually impaired people can navigate unknown areas by relying on the assistance of canes, other people, or specially trained guide dogs. The traditional ways of using guide dogs and long-cane only help to avoid obstacles, not to know where they are. The research presented in this paper introduces a mobile assistant navigation prototype to locate and direct blind people indoors. Since most of the existing navigation systems developed so far for blind people employ a complex conjunction of positioning systems, video cameras, location-based and image processing algorithms, we designed an affordable low-cost prototype navigation system for orienting and tracking the position of blind people in complex environments. The prototype system is based on the inertial navigation syst...
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Localization is one of the key aspects of wireless sensor networks (WSNs) that has attracted significant research interest. A wide variety of proposed approaches regarding the research topic has recently emerged; however, the majority of... more
Localization is one of the key aspects of wireless sensor networks (WSNs) that has attracted significant research interest. A wide variety of proposed approaches regarding the research topic has recently emerged; however, the majority of the existing approaches are limited by at least one of the following restrictions: inaccuracy, high cost, fast energy depletion, inappropriate indoor performance, or the requirement of an additional positioning hardware. In this paper, we present the research and development of a hybrid range-free WSN localization system, using the hop-count and received signal strength (RSS) methods. The proposed system is reliable and efficient indoors in terms of localization accuracy, cost and power consumption. Reference and target nodes have been designed and implemented, while real experiments have been carried out to assess the proposed system’s efficiency.
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Tracking systems using a high number of low cost sensor nodes have been proposed for use in diverse applications including civil, military, and wildlife monitoring applications. In tracking applications, each sensor node attempts to send... more
Tracking systems using a high number of low cost sensor nodes have been proposed for use in diverse applications including civil, military, and wildlife monitoring applications. In tracking applications, each sensor node attempts to send the target's location information to a sink node. Deploying a tracking system with a high number of sensor nodes results in the following limitations: high packet dropping rate, high congestion, transmission delay, and high power-consumption. Data aggregation schemes can reduce the number of ...
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Wireless sensor network applications have been deployed widely. Sensor networks involve sensor nodes which are very small in size. They are low in cost, and have a low battery life. Sensor nodes are capable of solving a variety of... more
Wireless sensor network applications have been deployed widely. Sensor networks involve sensor nodes which are very small in size. They are low in cost, and have a low battery life. Sensor nodes are capable of solving a variety of collaborative problems, such as, monitoring and surveillance. One of the critical components in wireless sensor networks is the localizing tracking sensor or mobile node. In this paper we will discuss the various location system techniques and categorize these techniques based on the communication between nodes ...
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Autonomous robot navigation has become a crucial concept in industrial development for minimizing manual tasks. Most of the existing robot navigation systems are based on the perceived geometrical features of the environment, with the... more
Autonomous robot navigation has become a crucial concept in industrial development for minimizing manual tasks. Most of the existing robot navigation systems are based on the perceived geometrical features of the environment, with the employment of sensory devices including laser scanners, video cameras, and microwave radars to build the environment structure. However, scene understanding is a significant issue in the development of robots that can be controlled autonomously. The semantic model of the indoor environment offers the robot a representation closer to the human perception, and this enhances navigation tasks and human–robot interaction. In this paper, we propose a low-cost and low-memory framework that offers an improved representation of the environment using semantic information based on LiDAR sensory data. The output of the proposed work is a reliable classification system for indoor environments with an efficient classification accuracy of 97.21% using the collected d...
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Location tracking systems are increasingly becoming the focus of research in the field of Wireless Sensor Network (WSN). Received Signal Strength (RSS)-based localization systems are at the forefront of tracking research applications.... more
Location tracking systems are increasingly becoming the focus of research in the field of Wireless Sensor Network (WSN). Received Signal Strength (RSS)-based localization systems are at the forefront of tracking research applications. Radio location fingerprinting is one of the most promising indoor positioning approaches due to its powerful in terms of accuracy and cost. However, fingerprinting systems require the collection of a large number of reference points in the tracking area to achieve reasonable localization accuracy. In this paper, we propose a fingerprinting localization approach based on a RSS technique. The proposed system does not require gathering a large number of reference points and offers good localization accuracy indoors. The implemented approach is based on dividing the tracking area into subareas and assigning a unique feature to each subarea through ranging the RSS values from different reference points. In order to test the proposed system's efficiency,...
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Coronavirus has affected millions of people worldwide, with the rate of infected people still increasing. The virus is transmitted between people through direct, indirect, or close contact with infected people. To help prevent the social... more
Coronavirus has affected millions of people worldwide, with the rate of infected people still increasing. The virus is transmitted between people through direct, indirect, or close contact with infected people. To help prevent the social transmission of COVID-19, this paper presents a new smart social distance system that allows individuals to keep social distances between others in indoor and outdoor environments, avoiding exposure to COVID-19 and slowing its spread locally and across the country. The proposed smart monitoring system consists of a new smart wearable prototype of a compact and low-cost electronic device, based on human detection and proximity distance functions, to estimate the social distance between people and issue a notification when the social distance is less than a predefined threshold value. The developed social system has been validated through several experiments, and achieved a high acceptance rate (96.1%) and low localization error (<6 m).
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The electric vehicle (EV) is one of the most important and common parts of modern life. Recently, EVs have undergone a big development thanks to the advantages of high efficiency, negligible pollution, low maintenance, and low noise.... more
The electric vehicle (EV) is one of the most important and common parts of modern life. Recently, EVs have undergone a big development thanks to the advantages of high efficiency, negligible pollution, low maintenance, and low noise. Charging stations are very important and mandatory services for electric vehicles. Nevertheless, they cause high stress on the electric utility grid. Therefore, renewable energy-sourced charging stations have been introduced. They improve the environmental issues of the electric vehicles and support remote area operation. This paper proposes the application of fuzzy control to an isolated charging station supplied by photovoltaic power. The system is modeled and simulated using Matlab/Simulink. The simulation results indicate that the disturbances in the solar insolation do not affect the electric vehicle charging process at all. Moreover, the controller perfectly manages the stored energy to compensate for the solar energy variations. Additionally, the...
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Air pollution is considered critical to people's comfort, health and safety. In both environments (indoor and outdoor) air pollution can be controlled using a small amount of inexpensive sensing units distributed across an area of... more
Air pollution is considered critical to people's comfort, health and safety. In both environments (indoor and outdoor) air pollution can be controlled using a small amount of inexpensive sensing units distributed across an area of interest for measuring the levels of different critical gasses such as CO, H 2 S and NO 2. The monitoring process is critical. The deployment of the Wireless Sensor Network offers an alternative solution by scattering a large number of disposable sensor nodes across an area of interest. Scientists may directly retrieve sensed data via a web server application from the sensor area. This paper offers an extensive review of the approaches available to support the environmental monitoring of the wireless sensor network.
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This paper presents a low-cost system architecture that has been proposed for automatically monitoring air quality indoors and continuously in real-time. The designed system is in pilot phase where 4 sensor nodes are deployed in indoor... more
This paper presents a low-cost system architecture that has been proposed for automatically monitoring air quality indoors and continuously in real-time. The designed system is in pilot phase where 4 sensor nodes are deployed in indoor environment, and data over 4 weeks has been collected and performance analysis and assessment are performed. Environmental data from sensor nodes are sent through ZigBee communication protocol. The proposed system is low in cost, and achieves low power consumption. Hardware and network architecture are presented in addition to real-world deployment.