Figure 9 - available via license: Creative Commons Attribution 4.0 International
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Greek pilot site's temperature sensor (left axis-purple color) and AC units power (right axis-green color) consumption data, 15 September 2021-25 September 2021.
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Building Information Modeling (BIM) is a critical element for the “digitalization” of the construction industry and can be exploited for energy-driven renovation procedures of existing residences. Advancing beyond a BIM with data-capturing capabilities that are limited to building static information only requires sensor data streams related to indo...
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Construction 4.0 is pushing the digitization of the construction industry. Lean Construction practices as methods to integrate people, processes, and technologies, together the Building Information Modeling (BIM) are helping to improve project efficiencies. The benefits of BIM are well recognized. Its use has become widespread for the design stage...
Citations
... Smadi's study [1], noted the importance of using testbeds for experimental analysis of smart grid technologies. Similarly, wireless sensor networks (WSNs) have been extensively explored in the context of smart homes for monitoring and controlling various systems and appliances [2,3]. ...
This paper presents the design and implementation of a versatile IoT testbed utilizing the openHAB platform, along with various wireless interfaces, including Z-Wave, ZigBee, Wi-Fi, 4G-LTE (Long-Term Evolution), and IR (Infrared Radiation), and an array of sensors for motion, temperature, luminance, humidity, vibration, UV (ultraviolet), and energy consumption. First, the testbed architecture, setup, basic testing, and collected data results are described. Then, by showcasing a typical day in the laboratory, we illustrate the testbed’s potential through the collection and analysis of data from multiple sensors. The study also explores the capabilities of the openHAB platform, including its robust persistence layer, event management, real-time monitoring, and customization. The significance of the testbed in enhancing data collection methodologies for energy assets and unlocking new possibilities in the realm of IoT technologies is particularly highlighted.
... It involves sensor data connected to indoor/outdoor environment and energy-usage parameters of the building, to deal with data-acquisition functionality that are related to building information. The collection of data involves the deployment of comprehensive WSNs capable of capturing and transmitting real-time data to cloud toolkit [13]. The effectiveness of WSN/BIM monitoring management system could be noticed in managing what is described as smart cities. BIM could be used to detect energy consumption and enhancing project resource productivity by eliminating unnecessary waste [14]. ...
... Smadi et al. (2021) [1], noted the importance of using testbeds for experimental analysis of smart grid technologies. Similarly, wireless sensor networks (WSNs) have been extensively explored in the context of smart homes for monitoring and controlling various systems and appliances [2,3]. ...
This paper presents the design and implementation of a versatile IoT testbed utilizing the openHab platform along with various wireless interfaces, including Z-Wave, ZigBee, WiFi, 4G-LTE, and IR, and an array of sensors for motion, temperature, luminance, humidity, vibration, UV, and energy consumption. First, the testbed architecture, setup, basic testing, and collected data results are described. Then, by showcasing a typical day in the laboratory, we illustrate the testbed's potential through the collection and analysis of data from multiple sensors. The study also explores the capabilities of the openHab platform, including its robust persistence layer, event management, real-time monitoring, and customization. The significance of the testbed in enhancing data-collection methodologies for energy assets and unlocking new possibilities in the realm of IoT technologies is particularly highlighted.
... The applying, technology, topology, and fee of sturdy WSNs are addressed to collect and ship actual-time information. The proposed real WSN considers different necessities within the field, constraints, and selections on the pilot destinations, and hence, it units the lines for similar institutions predicted by using the development enterprise for amassing dynamic data required for smart systems [22]. ...
Wireless Sensor Network (WSN) is a high potential technology used in many fields (agriculture, earth, environmental monitoring, resources union, health, security, military, and transport, IoT technology). The band width of each cluster head is specific, thus, the number of sensors connected to each cluster head is restricted to a maximum limit and exceeding it will weaken the connection service between each sensor and its corresponding cluster head. This will achieve the research objective which refers to reaching the state where the proposed system energy is stable and not consuming further more cost. The main challenge is how to distribute the cluster heads regularly on a specified area, that's why a solution was supposed in this research implies finding the best distribution of the cluster heads using a genetic algorithm. Where using an optimization algorithm, keeping in mind the cluster heads positions restrictions, is an important scientific contribution in the research field of interest. The novel idea in this paper is the crossover of two-dimensional integer encoded individuals that replacing an opposite region in the parents to produce the children of new generation. The mutation occurs with probability of 0.001, it changes the type of 0.05 sensors found in handled individual. After producing more than 1000 generations, the achieved results showed lower value of fitness function with stable behavior. This indicates the correct path of computations and the accuracy of the obtained results. The genetic algorithm operated well and directed the process towards improving the genes to be the best possible at the last generation. The behavior of the objective function started to be regular gradually throughout the produced generations until reaching the best product in the last generation where it is shown that all the sensors are connected to the nearest cluster head. As a conclusion, the genetic algorithm developed the sensors' distribution in the WSN model, which confirms the validity of applying of genetic algorithms and the accuracy of the results.
Wireless Sensor Network (WSN) is made up of minimal power devices (or) units spread over geographically separated locations. Sensors are grouped in the form of clusters. Every cluster has a key node known as the Cluster Head (CH). CH gathers sensed information out of its sensor nodes and transmits into a Base Station (BS). Sensors are indeed installed using non-replaceable batteries. WSN is concerned about its energy usage to reduce (or) minimize the consumption of energy as well as increase network lifetime. An improved upgraded technique is presented, which is accomplished by improving appropriate energy balancing in clusters across every sensor node in order to reduce power dissipation while networking connections. The enhanced technique was built by employing a well-known technique named cluster head selection. Accordingly, the energy consumption of WSN is reduced to prolong the network life cycle other than the network models. Furthermore, an efficient routing CH is optimized by the Average Fitness-based Harris Hawks Optimization (AF-HHO). In the WSN network, this proposed algorithm is used to locate neighbouring nodes with higher energy efficiency measurements. As a result, when compared to other conventional approaches, the simulation results demonstrate superior performance. Through the sink node, an optimal routing path for transferring data packets to neighbouring sensor nodes was discovered. The suggested technique is evaluated using energy consumption, network lifespan, and residual energy performance estimations.
