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Energy Harvesters are used to Power Nodes in Wireless Sensor Networks
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International Journal of Sensor Networks and Data Communications

ISSN: 2090-4886

Open Access

Editorial - (2022) Volume 11, Issue 2

Energy Harvesters are used to Power Nodes in Wireless Sensor Networks

Aditya Panigrahi*
*Correspondence: Aditya Panigrahi, Department of Computer Science, University of York, UK, Email:
Department of Computer Science, University of York, UK

Received: 07-Feb-2022, Manuscript No. sndc-22-58538; Editor assigned: 09-Feb-2022, Pre QC No. P-58538; Reviewed: 14-Feb-2022, QC No. Q-58538; Revised: 19-Feb-2022, Manuscript No. R-58538; Published: 24-Feb-2022 , DOI: 10.37421/2090-4886.2022.11.147
Citation: Panigrahi, Aditya. “Energy Harvesters are used to Power Nodes in Wireless Sensor Networks.” J Sens Netw Data Commun 11 (2022): 147. DOI: 10.37421/2090-4886.2022.11.147
Copyright: © 2022 Panigrahi A. This is an open-access article distributed under the terms of the creative commons attribution license which permits unrestricted use, distribution and reproduction in any medium, provided the original author and source are credited.

Editorial

Creating innovation answers for oversee energy utilization in structures effectively is a region that has drawn in much consideration from specialists lately. In existing structures, such advancements should be used without diminishing the indoor solace of the clients (basically visual and warm solace), which could be accomplished by means of enhancing the activity and control frameworks of hardware, for example, warming ventilation-cooling (HVAC), lighting, shut circuit TV (CCTV), access control, fire wellbeing, security, and electric machines. Resolving this issue is useful to society since structures are among the biggest energy-consuming frameworks around the world. As indicated by the 2019 Global Status Report for Buildings and Construction Sector, around 30% of the worldwide end-use energy utilization in 2018 was because of private and non-residential structures (International Energy Agency, which likewise created around 28% of worldwide energy-related CO2 outflows. The power utilization of the structure area has been around 49% of the world's aggregate, with private structures consuming 27% and business and public structures consuming 22 percent [1-5].

Central air frameworks consume the most noteworthy energy in structures, with around half of the energy utilization in structures in created nations like the US and UK. After HVAC frameworks, lighting frameworks are the secondbiggest power purchaser in structures with around 19%. Further developing the energy effectiveness in the two sorts of frameworks in structures would address critical monetary reserve funds and decrease of CO2 emanations. Consequently, essential to utilize creative advances work on computerized and clever control of the multitude of frameworks that comprise a structure. The plan and execution of wise structures is an option for diminishing energy utilization, working expenses, and CO2 outflows. Normally, shrewd structure control frameworks are responsive, contrasted with the prevalent versatile controls in brilliant structures. Shrewd structures should be visible as energycreating substances that can perform load decrease, top shaving, and load moving, load decrease during power outage and brownout occasions, lattice solidness, among different purposes. A thorough treatment of smart structures isn't inside the extent of the current work. Making a structure ''more smart'' would begin with the utilization of control frameworks that permit checking ongoing tasks and ideally control electrical burdens, for the most part lighting and HVAC. These capacities could be accomplished by building energy the board frameworks (BEMSs) or building robotization control frameworks (BACSs) in light of regulator organizations. These regulators should be dependable, protected, versatile, and financially savvy since a wrong control or unfortunate framework the board could fundamentally diminish the structure execution and effect the economy and the climate. Additionally, the constant improvement of these parts will permit a smoother coordination of a structure with utilities, other clever structures, brilliant matrices, and other electrical and innovation frameworks. Essentially, following the improvement of micro grids and savvy matrices, shrewd structures can fuse dispersed energy assets (DERs), including disseminated age (DG) and conveyed stockpiling (DS). The headway of web of things (IoT), AI, huge information, distributed computing, and control calculations are carrying savvy structures nearer to becoming brilliant structures In outline, all the expected robotization inside a keen structure is represented by networks, correspondence conventions, control frameworks and gear, functional information obtaining, information capacity, and sensors. Sensors are principal gadgets for the computerization and control of savvy structures. For instance, inhabitance sensors can assist with controlling frameworks of structures to accomplish potential energy investment funds somewhere in the range of 15% and 40% of absolute energy utilization and 56% on HVAC frameworks. Besides, lighting control can accomplish potential energy investment funds up to 75%. There are an assortment of sensors accessible in the market which are utilized in structures for estimating factors like temperature, stickiness, CO2 , unpredictable natural mixtures, inhabitance, nearness, pressure, stream, commotion, vibration, and light force. The ideal area, suitable arrangement, and appropriate choice of these gadgets accurately screen the above factors.

Conflict of Interest

None.

References

  1. Abdu, Abdullahi Ibrahim, and Muhammed Salamah. “Energy-aware transmission scheme for wireless sensor networks.” In Recent Trends in Wireless and Mobile Networks (2011): 135--144
  2. Google Scholar, Crossref

  3. Deng, Jing, Yunghsiang S. Han, Wendi B. Heinzelman, and Pramod K. Varshney, "Scheduling sleeping nodes in high density cluster-based sensor networks." Mob Netw Appl 28 (2005).
  4. Google Scholar, Crossref

  5. Akyildiz, Ian F., Weilian Su, Yogesh Sankarasubramaniam, and Erdal Cayirci. "A Survey of Sensor Networks” IEEE Communication Mag 40 (2002): 102-114.
  6. Google Scholar, Crossref

  7. Deng Jing, Yunghsiang S. Han, Wendi B. Heinzelman and Pramod K. Varshney, "Balanced-energy Sleep Scheduling Scheme for High Density Cluster-based Sensor Networks." Comput Commun 8 (2005).
  8. Google Scholar, Crossref

  9. V. Raghunathan, A. Kansal, J. Hsu, J. Friedman and M. Srivastava, "Design Considerations for Solar Energy Harvesting Wireless Embedded Systems." IPSN (2005): 457-462
  10. Google Scholar, Crossref

Google Scholar citation report
Citations: 343

International Journal of Sensor Networks and Data Communications received 343 citations as per Google Scholar report

International Journal of Sensor Networks and Data Communications peer review process verified at publons

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