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In the recent few years, due to its significant deployment to meet global demand for smart cities, the Internet of Things (IoT) has gained a lot of attention. Environment energy harvesting devices, which use ambient energy to generate electricity, could be a viable option in near future for charging or powering stand-alone IoT sensors and electronic devices. The key advantages of such energy harvesting gadgets are that they are environmentally friendly, portable, wireless, cost-effective, and compact. It is significant to propos and fabricate an improved, high-quality, economical, and efficient energy harvesting systems to overcome power supply to tiny IoT devices at the remote locations. In this article, various types of mechanisms for harvesting renewable energies that can power sensor enabled IoT locally, as well as its associated wireless sensor networks (WSNs), are reviewed. These methods are discussed in terms of their advantages and applications, as well as their drawbacks and limitations. Furthermore, methodological performance analysis for the decade 2005 to 2020 is surveyed in order to identify the methods that delivered high output power for each device. Furthermore, the outstanding breakthrough performances of each of the aforementioned micro-power generators during this time period are emphasized. According to the research, thermoelectric modules can convert up to 2500×10^(-3) W/cm^2, thermo-photovoltaic 10.9%, piezoelectric 10,000 mW/cm^3 and microbial fuel cell 6.86 W/m^2 of energy. Doi: 10.28991/esj-2021-SP1-08 Full Text: PDF

Minimum Redundancy Linear Arrays (MRLAs) and Uniform Linear Arrays (ULAs) investigation conducted with the possibility of using them in future 5G smart devices. MRLAs are designed to minimize the number of sensor pairs with the same spatially correlated delay. It eliminates selected antennas from the entire composite antenna array and preserves all possible antenna spacing. MRLAs have attractive features for linear sparse arrays, even if the built-in surface is deformed, it works without problems. To our knowledge, MRLAs have not been applied to smart devices so far. In this work, a 7-element ULAs and 4-element MRLAs (same aperture) were used for the simulation. The Half Power Beamwidth (HPBW) is 0.666 and the Null-to-Null Beamwidth ( ) is 1.385 in ψ-space. In comparison, the standard 4-element arrays are 1.429 and 3.1416, while the standard 7-element linear arrays are 0.801 and 1.795 respectively. Experimental results show that 4-element MLRAs have a narrower mean beam, much higher sidelobes and shallow nulls. Therefore, in terms of main lobe features, 4- elements MRLAs have an improvement over the standard 7-element ULAs. Doi: 10.28991/esj-2021-SP1-05 Full Text: PDF

Large numbers of mobile wireless nodes that can move randomly and join or leave the network at any moment make up mobile ad-hoc networks. A significant number of messages are delivered during information exchange in populated regions because of the Internet of Things' (IoT) exponential increase in connected devices. Congestion can increase transmission latency and packet loss by causing congestion. More network size, increased network traffic, and high mobility that necessitate dynamic topology make this problem worse. An adaptive Multipath Multichannel Energy Efficient (AMMEE) routing strategy is proposed in this study, in which route selection strategies depend on forecasted energy consumption per packet, available bandwidth, queue length, and channel utilization. While multichannel uses a channel-ideal assignment process to lessen network collisions, multipath offers various paths and balances network strain. The link bandwidth is split up into a few sub-channels in the multichannel mechanism. To reduce network collisions, several source nodes simultaneously access the channel bandwidth. The cooperative multipath multichannel technique offers several paths from a single source or from several sources to the destination without colliding or becoming congested. The AMMEE routing approach is the basis for path selection. A load- and bandwidth-aware routing mechanism in the proposed AMMEE chooses the path based on node energy and forecasts their lifetime, which improves network dependability. The outcome demonstrates a comparative analysis of various multichannel medium access control (MMAC) techniques, including Parallel Rendezvous Multi Channel Medium Access Protocol (PRMMAC), Quality of Service Ad hoc On Demand Multipath Distance Vector (QoS-AOMDV), Q-learning-based Multipath Routing (QMR), and Topological Change Adaptive Ad hoc On-demand Multipath Distance Vector (TA-AOMDV) and the proposed AMMEE method. The results show that the AMMEE approach outperforms alternative systems. Doi: 10.28991/ESJ-2024-08-01-018 Full Text: PDF

"The intersection of artificial intelligence (AI) and digital twin technology presents a problem and an unparalleled opportunity for transformation. Businesses grapple with the need for operational excellence, innovation, and a competitive edge, all while navigating the intricate web of data analytics, decision-making, and real-time monitoring. In response to these challenges, Harnessing AI and Digital Twin Technologies in Businesses emerges as an example of insight and guidance, offering a comprehensive exploration of the complementary connection between AI and digital twin technology. In a world where the convergence of these powerful tools transforms business intelligence, enabling initiative-taking decision-making and dynamic simulations. This book serves as a solution for decision-makers, technologists, and researchers seeking to not only understand but harness the potential of AI-powered digital twins to enhance productivity, creativity, and judgment in their operations."--

The concept of project success has evolved from the perspective of conforming to the project triangle to that of benefiting the environment, and then from the perspective of the following generation. Scientists increasingly assert that successful projects require a set of criteria that include such item(s) as future potential. The meaning of project success varies depending on where it is executed. The purpose of this study is to identify whether projects with future potential have a certain effect on indicators of the Global Competitiveness Index (GCI) of the Republic of Kazakhstan (RK) and what other success criteria are inherent in such projects. By using the method of descriptive analysis of data collected from 107 experts and analyzing 19 influential projects, the study revealed that projects oriented towards the future have a significant impact on the indicators of the GCI in the RK. This finding confirms the necessity of considering the long-term sustainability and social significance of projects when assessing their successes. Additionally, a specific combination of success criteria that contributes most to this impact was identified. This research provides a brand-new understanding of project success criteria in the context of their impact on the GCI and emphasizes the importance of considering future potential in project planning and evaluation. Doi: 10.28991/ESJ-2024-08-02-012 Full Text: PDF