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In recent times, advances in wireless technology have allowed researchers and practitioners to stopover in areas that were unimaginable a few short decades ago. The field of Wireless sensor networks (WSNs) merges many of functions like sensing, computation, and communication into a single tiny device in order
to fatherly have these tiny sensor dev...
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This paper investigates real-life environmental monitoring applications based on Wireless Sensor Networks (WSNs). Wireless sensor networking is an emerging technology, which through the research in the labs and the real deployments has proved to be a significant and valuable tool for scientists in their effort to explore various environmental pheno...
Citations
... WSNs have found applications in several domains, including healthcare monitoring [3][4][5][6][7][8][9], environmental monitoring [10][11][12][13][14], military monitoring [15][16][17], vehicle monitoring [18,19], industrial [20,21], agriculture [22][23][24], and urban monitoring applications [25]. ese numerous application areas have made WSN areas of intense research in wireless communications [26]. ...
Wireless Sensor Networks (WSNS) have become an indispensable tool in this epoch of technological advancements, particularly for progress made in the Internet of things. Wireless sensor nodes are deployed to collect and transmit vital data from the environment to a base station for analysis. Nevertheless, the limited battery power of the sensor nodes is rapidly drained when they stay awake for an extended period. Research has shown that significant sources of energy dissipation of sensor nodes are idle listening, packet collision, control overhead, and overhearing. One optimal solution is employing a low duty cycle mac protocol, particularly the sensor mac (SMAC) protocol. It is essential to have a detailed knowledge of the challenges identified in SMAC and solutions suggested to mitigate these challenges and the future directions. In this paper, we review techniques in SMAC protocols implemented in WSNS. In particular, we provide highlights of recent developments in the schemes used in SMAC for mitigating the challenges in SMAC and present research gaps in SMAC protocol. Finally, we discuss open issues that need to be addressed to advance the design and implementation of SMAC in WSN applications.
... The sensing element for earthquake detection is a wireless acceleration sensor device [54]. Dissemination of information about the likelihood of an earthquake must occur at the appropriate time [55]. A large mass of rock, rubble, or earth slides down a slope, which is referred to as a landslide. ...
Wireless sensor networks (WSNs) have become ubiquitous, permeating every aspect of human life. In environmental monitoring applications (EMAs), WSNs are essential and provide a holistic view of the deployed environment. Physical sensor devices and actuators are connected across a network in environmental monitoring applications to sense vital environmental factors. EMAs bring together the intelligence and autonomy of autonomous systems to make intelligent decisions and communicate them using communication technologies. This paper discusses the various architectures developed for WSNs in environmental monitoring applications and the support for specific design goals, including machine learning in WSNs and its potential in environmental monitoring applications.
... In terms of targets tracking many techniques presented such as (i) static clustering [17] had proposed three mechanisms for target tracking based on clustering. (ii) dynamic clustering [18][19][20] had proposed a clustering-based system for detecting unanticipated intrusions. (iii) utilizing prediction approach to improve target tracking such as Kalman filter, practical filter. ...
... In terms of targets tracking many techniques presented such as (i) static clustering [17] had proposed three mechanisms for target tracking based on clustering. (ii) dynamic clustering [18][19][20] had proposed a clustering-based system for detecting unanticipated intrusions. (iii) utilizing prediction approach to improve target tracking such as Kalman filter, practical filter. ...
... In terms of targets tracking many techniques presented such as (i) static clustering [17] had proposed three mechanisms for target tracking based on clustering. (ii) dynamic clustering [18][19][20] had proposed a clustering-based system for detecting unanticipated intrusions. (iii) utilizing prediction approach to improve target tracking such as Kalman filter, practical filter. ...
Wireless Sensor Network (WSNs) provides promising solutions for monitoring in several domains including industrial monitoring and control, home automation and smart cities, etc. There are numerous restrictions on the current development of target detection and tracking algorithms which makes them unsuitable or effective for indoor use. Such constraints include changes in the direction and changing target speeds, missing a target, and target dynamics. These issues come with difficulty in detection and tracking multiple targets. Moreover, the majority of the target tracking algorithms were presented on the conditions that the target is typically smooth with no unexpected changes that are difficult absolutely. Moreover, sensing coverage considers the crucial issue in a wireless sensor network. This paper implies an algorithm for detection and tracking of moving targets (intruders) for an indoor environment based on the probabilistic model utilizing WSN for safety and security. A mathematical model is presented to determine the optimum number of sensor nodes needed. The findings of the simulation showed that the MTDT algorithm provides a low missing target rate of less than 0.7 % for worst-case and can be utilized for different kinds of environment scenarios.
... For the convergence of enabling technologies to be possible, however, there needs to be a network of wireless sensors for detection and "smart environmental monitoring" that effectively links cyber-physical environments (cf. [25]). In their turn, sensors cannot function in isolation. ...
Smart city strategies developed by cities around the world provide a useful resource for insights into the future of smart development. This study examines such strategies to identify plans for the explicit deployment of artificial intelligence (AI) and robotics. A total of 12 case studies emerged from an online keyword search representing cities of various sizes globally. The search was based on the keywords of “artificial intelligence” (or “AI”), and “robot,” representing robotics and associated terminology. Based on the findings, it is evident that the more concentrated deployment of AI and robotics in smart city development is currently in the Global North, although countries in the Global South are also increasingly represented. Multiple cities in Australia and Canada actively seek to develop AI and robotics, and Moscow has one of the most in-depth elaborations for this deployment. The ramifications of these plans are discussed as part of cyber–physical systems alongside consideration given to the social and ethical implications.
... There is no any controlling part in the system. They used different sensor such as temperature, light, sound etc. Nashwa El-Bendary Saumya Banerjee, Mohamed Mostafa M. Fouad [5] proposed work on the wireless sensor network. By using WSN technology they built a system which is used in smart environment monitoring. ...
Field instruments used in boiler water treatment plant are not able to access remotely and only able to control through central location Also the data are able to access through the internet only in the particular area. If any data lag or system failure occurs then it can be control only in the plant area. This becomes complex and cannot be applicable for all situation. To avoid such complexity happened due to system error and to monitor the system parameter remotely, a cloud based system from Siemen is used to connects plant, system and machines by IoT with advanced analytics and practically tested in Technocart Automation plant located in Ambattur, TamilNadu, India. This gives advance solution for monitoring the industrial parameter anywhere using Siemens Mindsphere and Mind connect nano Software.
... In the system sensor nodes are used to sense the data and then transmit this data to the microcontroller. This chapter provides an understanding about the techniques and features which researchers and system designers should keep in mind for successful deployments and operation of real smart environmental monitoring systems [6]. Anjaiah Guthi(2016) implemented a Noise and Air Pollution Monitoring System using Internet of Things (IoT). ...
Time series analysis and prediction have been widely accepted in various domains from last two decades. Business analytics, Medical drugs & pharmaceutical, Dynamic Marketing, Weather forecasting, Pollution measures, financial portfolio analysis and Stock market prediction are the favorite domains among research communities under time series analysis. Since air quality is one of the paramount factors which make life possible on earth and monitoring air quality data as time series analysis is a one of prime area. The most affected air quality parameters on health are carbon monoxide (CO),carbon dioxide (CO2), Ammonia(NH3) and Acetone ((CH3)2CO). In this paper we have taken the sensor’s data of three specific locations of Delhi and National Capital Region (NCR) and predict air quality of next day using linear regression as machine learning algorithm. Model is evaluated through four performance measures Mean Absolute Error (MAE), Mean Square Error (MSE), Root Mean Square Error (RMSE) and Mean Absolute Percentage Error (MAPE). The study further assesses with benchmark model and obtains significant results.
... As sensors are capable of accurately sensing temperature, light, air pollution, and moving objects, WSN's technology become the promising solutions for in smart and efficient monitoring [1], [2]), [3] [4], [5], [6], [7]. With the use of WSNs, smart, safer, and secure environment for residents can be ensured. ...
... Besides that, the average simulation results of the proposed system for different number of targets fixed and high even while there are multi-targets in the monitoring area. Moreover, by compared the results of our proposed system with the results of MHT in case of multi-targets (2,3,4,5) in the monitoring area. The comparison showed that the difference between our system and MHT is very large. ...
The current developed event detection and tracking systems
have several limitations that make them not suitable or
efficient to be utilized in smart homes. These limitations
include dealing with direction changes and varying speeds of
an evolving events, node fault tolerance, energy consumption,
missing of target, tracking precision, dynamicity of the target,
and prediction accuracy. The situation become more difficult
in term of multi-targets. Efficient tracking after the detection
of an event based on robust data control and management
would definitely help in making reliable distributed control
decisions, therefore a reliable system is highly needed. In this
paper we proposed a system for monitoring and detecting of
continuous moving objects according to certain requirements
and specifications that are related to smart home concept. The
system can be detecting and tracking multi objects in the
monitoring area that are moving randomly with varying
speed by using ordinary sensors. The proposed system able to
collect and analysis the data during their development in time
and space. In this paper have been used a dynamic sensing
model for accurate observation and delectability of the event.
The simulation results of the proposed system show high
detection and tracking accuracy for detection and tracking
multi continues moving objects. The proposed system shows
high tracking accuracy in term of single reach to 97 % and
multi-targets (up to 5) reach to more than 94 %
... The integration of wireless sensor networks (WSNs) in agriculture is a recent concept, which has leads to what is called precision agriculture. The agricultural WSNs monitoring of the air temperature, air humidity, soil temperature, soil moisture, leaf wetness, atmospheric pressure, solar radiation, wind direction, amount rainfall and etc. [8]. ...
Modern technologies of growing different plants types in greenhouses envisage automated systems use for monitoring climatic parameters, on which the ripening of fruits and yields depend. At the development and application of such automated systems, the focus is on measuring the accuracy of temperature and humidity soil, whereas to determine the level of illumination used sensors, that measure the total illumination or Photosynthetic Active Radiation (400-700 nm) with error up to 20%. Under conditions of insufficient photon flux density, even at the optimal moisture level and temperature in the greenhouse, fruiting and crop yields may not achieve high performance. This article proposes a greenhouse lighting control system in which the LI-200R Pyranometer and LI-190R-BL Quantum Sensor measure not only total illumination from the wavelength of 400-1000 nm, but also PPFD from a wavelength of 400-700 nm. Light Sensor Amplifier provides an increase in the source signal of the measuring sensors and reduces their measurement error to 1%. The applied SMART Connectivity Platform ESP8266 Version ESP 07 is more robust to interference and ensures the transfer of measured data to the server. Created software application for smartphones with Android OS, ensures remote user access to the database via the Internet for remote control and analysis of climatic indicators in the greenhouse. The proposed illumination control system in the greenhouse contributes to the improvement of precision farming.
