Skip to content
2000
  1. Home
  2. A-Z Publications
  3. Recent Patents on Mechanical Engineering
  4. Fast Track Articles
  5. Fast Track Article
image of Performance Analysis of IoT-based Temperature Monitoring Box Type Solar Cooker: A Multi-objective Optimization Approach

Abstract

Background

The idea behind the Internet of Things is to bring the virtual world into the physical one by connecting commonplace items. With the help of the Internet of Things (IoT), it is possible to remotely sense or control objects through preexisting network infrastructure. This opens up possibilities for computer-based systems to integrate with the physical world, which in turn improves efficiency, accuracy, and economic benefit while reducing the need for human intervention.

Objective

The purpose of this patent study is to investigate how a (NSGA-II) multi-objective genetic algorithm might be utilized to optimize the execution of an Internet of Things (IoT) temperature monitoring Box-Type Solar Cooker (BTSC). To determine the best set of output parameters for an IoT temperature monitoring box-type solar cooker, (NSGA-II) multi-objective genetic algorithms are used to perform optimizations of the figure of merits (F), cooking power, cooker efficiency, and final water temperature.

Methods

The present research work involves the development of a Wi-Fi module system integrated with a smart temperature monitoring system for a BTSC. Keeping track of the temperature data from different locations in the BTSC through the IoT system was the primary objective of this project. A waterproof temperature sensor (DS18B20) was used to keep monitoring. After that, the data was shown on an LCD, stored on a microSD card, and made available through a smartphone. The Blynk Applications' IoT was employed. Using existing data, regression-based computational models are developed to describe the complex correlations between the decision-processing parameters and the input parameters of an IOT-based solar cooker. These models are applied in the objective functions after determining that a genetic algorithm is more appropriate for the problem. To forecast the optimal values about the figure of merits (F), cooking power, cooker efficiency, and final water temperature, the Pareto fronts have been developed.

Results

We compare the values of response variables that were gathered experimentally with the values that were predicted by NSGA-II. The predicted values are found to be quite close to experimental values. This indicates that the multi-objective optimization method, as used in this study, has very good prediction performance. The test results are graphically shown using the error bar. Therefore, it is clear that the optimization process used to adjust the parameters of the solar cooker's performance has been quite effective. According to the findings of the experiment, the temperature at which a cooking pot remained stagnant on average was 158°C. It was determined that the cooker was of class A based on the values of the first figure of merit (F), the second figure of merit (F), and the cooking power (P), which were respectively 0.132, 0.359, and 86.108 W. Therefore, the thermal efficiency of the IoT-base temperature monitoring box type solar cooker is 39.99%.

Conclusion

The findings of this inquiry furthermore produced the outcome that the model provided can be applied conveniently with a confidence level of 95% to calculate the figure of merits (F), cooking power, cooker efficiency, and final water temperature value of an Internet of Things-based temperature monitoring BTSC. The performance of IoT-based BTSC is optimized by providing real-time monitoring and data visualization, ultimately improving their efficiency and reliability. This research provides an educational tool to promote awareness and understanding of renewable energy sources and their potential benefits.

© 2024 Bentham Science Publishers
Loading

Article metrics loading...

/content/journals/meng/10.2174/0122127976351079241209120103
2024-12-30
2025-01-19

  • From This Site

    /content/journals/meng/10.2174/0122127976351079241209120103
    dcterms_title,dcterms_subject,pub_keyword
    -contentType:Contributor -contentType:Concept -contentType:Institution
    10
    5
Loading full text...

Full text loading...

References

  1. Goyal R.K. Eswaramoorthy M. Thermal performance enhancement on a box-type solar cooker using a triangular fin over a conventional cooking pot. Sol. Energy 2023 258 339 350 10.1016/j.solener.2023.03.053
    [Google Scholar]
  2. Aramesh M. Ghalebani M. Kasaeian A. Zamani H. Lorenzini G. Mahian O. Wongwises S. A review of recent advances in solar cooking technology. Renew. Energy 2019 140 419 435 10.1016/j.renene.2019.03.021
    [Google Scholar]
  3. Chatelain T. Mauree D. Taylor S. Bouvard O. Fleury J. Burnier L. Schüler A. Solar cooking potential in Switzerland: Nodal modelling and optimization. Sol. Energy 2019 194 788 803 10.1016/j.solener.2019.10.071
    [Google Scholar]
  4. Khatri R. Goyal R. Sharma R.K. Advances in the developments of solar cooker for sustainable development: A comprehensive review. Renew. Sustain. Energy Rev. 2021 145 111166 10.1016/j.rser.2021.111166
    [Google Scholar]
  5. Hoffmann T.M. Solar oven positioning. US Patent 20140251314A1 2014
  6. Wang J. Solar Steam Cooker. US Patent 20120263845A1 2012
  7. Sarangi A. Sarangi A. Sahoo S.S. Nayak J. Mallik R.K. Advancements and global perspectives in solar cooking technology: A comprehensive review. Energy Nexus 2024 13 100266 10.1016/j.nexus.2023.100266
    [Google Scholar]
  8. Koshti B. Dev R. Bharti A. Narayan A. Comparative performance evaluation of modified solar cookers for subtropical climate conditions. Renew. Energy 2023 209 505 515 10.1016/j.renene.2023.04.021
    [Google Scholar]
  9. Kagale P. Jangamshetti S.H. Development and testing of iot based monitoring interface for solar box cooker. IEEE Bangalore Humanitarian Technology Conference (B-HTC) Vijiyapur, India, 08-10 Oct. 2020, pp. 1-4. 10.1109/B‑HTC50970.2020.9297950
    [Google Scholar]
  10. Patil S.M. Vijayalashmi M. Tapaskar R. IoT based solar energy monitoring system. International Conference on Energy, Communication, Data Analytics and Soft Computing (ICECDS) Chennai, India, 01-02 Aug. 2017, pp. 1574-1579. 10.1109/ICECDS.2017.8389711
    [Google Scholar]
  11. Daniel F. Collapsible cooking stove. US Patent 10598384B2 2020
  12. Walters A. Solar oven and method of solar cooking. US Patent 20110206818A1 2011
  13. Tiwari A. Kumar N. Banerjee M.K. Applications of genetic algorithm in prediction of the best achievable combination of hardness and tensile strength for graphene reinforced magnesium alloy (AZ61) matrix composite. Results Control Optim. 2024 14 100334 10.1016/j.rico.2023.100334
    [Google Scholar]
  14. Mohammed B.A. Al-Shareeda M.A. Alsadhan A.A. Al-Mekhlafi Z.G. Sallam A.A. Al-Qatab B.A. Alshammari M.T. Alayba A.M. Efficient blockchain-based pseudonym authentication scheme supporting revocation for 5G-assisted vehicular fog computing. IEEE Access 2024 12 33089 33099 10.1109/ACCESS.2024.3372390
    [Google Scholar]
  15. Al-Mekhlafi Z.G. Al-Shareeda M.A. Manickam S. Mohammed B.A. Alreshidi A. Alazmi M. Alshudukhi J.S. Alsaffar M. Rassem T.H. Efficient authentication scheme for 5G-enabled vehicular networks using fog computing. Sensors (Basel) 2023 23 7 3543 10.3390/s23073543 37050601
    [Google Scholar]
  16. Al-Mekhlafi Z.G. Al-Shareeda M.A. Manickam S. Mohammed B.A. Alreshidi A. Alazmi M. Alshudukhi J.S. Alsaffar M. Alsewari A. Chebyshev polynomial-based fog computing scheme supporting pseudonym revocation for 5G-enabled vehicular networks. Electronics (Basel) 2023 12 4 872 10.3390/electronics12040872
    [Google Scholar]
  17. Mohammed B.A. Al-Shareeda M.A. Manickam S. Al-Mekhlafi Z.G. Alayba A.M. Sallam A.A. ANAA-Fog: A novel anonymous authentication scheme for 5G-enabled vehicular fog computing. Mathematics 2023 11 6 1446 10.3390/math11061446
    [Google Scholar]
  18. Issac G.A. Mary A.J. Validation Scheme for VANET 2nd International Conference on Signal Processing and Communication (ICSPC) Coimbatore, India, 29-30 March 2019, pp. 11-15. 10.1109/ICSPC46172.2019.8976645
    [Google Scholar]
  19. Ali I. Hassan A. Li F. Authentication and privacy schemes for vehicular ad hoc networks (VANETs): A survey. Vehicular Communications 2019 16 45 61 10.1016/j.vehcom.2019.02.002
    [Google Scholar]
  20. Almazroi A.A. Alkinani M.H. Al-Shareeda M.A. Alqarni M.A. Almazroey A.A. Gaber T. FC-LSR: Fog computing-based lightweight sybil resistant scheme in 5G-enabled vehicular networks. IEEE Access 2024 12 30101 30112 10.1109/ACCESS.2024.3368393
    [Google Scholar]
  21. Almazroi A.A. Alqarni M.A. Al-Shareeda M.A. Alkinani M.H. Almazroey A.A. Gaber T. FCA-VBN: Fog computing-based authentication scheme for 5G-assisted vehicular blockchain network. Internet of Things 2024 25 101096 10.1016/j.iot.2024.101096
    [Google Scholar]
  22. Almazroi A.A. Alqarni M.A. Al-Shareeda M.A. Manickam S. L-CPPA: Lattice-based conditional privacy-preserving authentication scheme for fog computing with 5G-enabled vehicular system. PLoS One 2023 18 10 e0292690 10.1371/journal.pone.0292690 37889892
    [Google Scholar]
  23. Almazroi A.A. Aldhahri E.A. Al-Shareeda M.A. Manickam S. ECA-VFog: An efficient certificateless authentication scheme for 5G-assisted vehicular fog computing. PLoS One 2023 18 6 e0287291 10.1371/journal.pone.0287291 37352258
    [Google Scholar]
  24. Xu S. Momin M. Ahmed S. Hossain A. Veeramuthu L. Pandiyan A. Kuo C.C. Zhou T. Illuminating the brain: Advances and perspectives in optoelectronics for neural activity monitoring and modulation. Adv. Mater. 2023 35 42 2303267 10.1002/adma.202303267 37726261
    [Google Scholar]
  25. Xu S. Scott K. Manshaii F. Chen J. Heart-brain connection: How can heartbeats shape our minds? Matter 2024 7 5 1684 1687 10.1016/j.matt.2024.03.015
    [Google Scholar]
  26. Xu S. Liu Y. Lee H. Li W. Neural interfaces: Bridging the brain to the world beyond healthcare. Exploration 2024 4 5 20230146 10.1002/EXP.20230146
    [Google Scholar]
  27. Xu S. Xiao X. Manshaii F. Chen J. Injectable fluorescent neural interfaces for cell-specific stimulating and imaging. Nano Lett. 2024 24 28 8793 10.1021/acs.nanolett.4c02798 38967553
    [Google Scholar]
  28. Ma H. Zhang Y. Sun S. Liu T. Shan Y. A comprehensive survey on NSGA-II for multi-objective optimization and applications. Artif. Intell. Rev. 2023 56 12 15217 15270 10.1007/s10462‑023‑10526‑z
    [Google Scholar]
  29. Ali I.M. Sallam K.M. Moustafa N. Chakraborty R. Ryan M. Choo K.K.R. An automated task scheduling model using non-dominated sorting genetic algorithm II for fog-cloud systems. IEEE Trans. Cloud Comput. 2022 10 4 2294 2308 10.1109/TCC.2020.3032386
    [Google Scholar]
  30. Bi H. Lu F. Duan S. Huang M. Zhu J. Liu M. Two-level principal–agent model for schedule risk control of IT outsourcing project based on genetic algorithm. Eng. Appl. Artif. Intell. 2020 91 103584 10.1016/j.engappai.2020.103584
    [Google Scholar]
  31. Lu F. Bi H. Huang M. Duan S. Simulated annealing genetic algorithm based schedule risk management of IT outsourcing project. Math. Probl. Eng. 2017 2017 1 6916575 10.1155/2017/6916575
    [Google Scholar]
  32. Mawire A. Abedigamba O.P. Worall M. Experimental comparison of a DC PV cooker and a parabolic dish solar cooker under variable solar radiation conditions. Case Stud. Therm. Eng. 2024 54 103976 10.1016/j.csite.2024.103976
    [Google Scholar]
  33. Al-Nehari H.A. Mohammed M.A. Odhah A.A. Al-attab K.A. Mohammed B.K. Al-Habari A.M. Al-Fahd N.H. Experimental and numerical analysis of tiltable box-type solar cooker with tracking mechanism. Renew. Energy 2021 180 954 965 10.1016/j.renene.2021.08.125
    [Google Scholar]
  34. Bhatti K.A. Asghar S. Rauf B. Qureshi I.A. A multi-objective integrated PID controller combined with NSGA-III for minimizing congestion in WSNs. Wirel. Netw. 2024 30 3 1423 1439 10.1007/s11276‑023‑03579‑z
    [Google Scholar]
  35. Saini P. Pandey S. Goswami S. Dhar A. Mohamed M.E. Powar S. Experimental and numerical investigation of a hybrid solar thermal-electric powered cooking oven. Energy 2023 280 128188 10.1016/j.energy.2023.128188
    [Google Scholar]
  36. Bhatti K.A. Asghar S. Naz S. Multi-objective fuzzy krill herd congestion control algorithm for WSN. Multimedia Tools Appl. 2024 83 1 2093 2121 10.1007/s11042‑023‑15200‑8
    [Google Scholar]
  37. Zhou C. Wang Y. Li J. Ma X. Li Q. Yang M. Zhao X. Zhu Y. Simulation and economic analysis of an innovative indoor solar cooking system with energy storage. Sol. Energy 2023 263 111816 10.1016/j.solener.2023.111816
    [Google Scholar]
  38. Washington R. Garmatyuk D. Mudaliar S. Narayanan R.M. Many-objective radarcom signal design via NSGA-II genetic algorithm implementation and simulation analysis. Remote Sens. (Basel) 2022 14 15 3787 10.3390/rs14153787
    [Google Scholar]
  39. Agushaka J.O. Ezugwu A.E. Abualigah L. Dwarf M.O.A. Dwarf mongoose optimization algorithm. Comput. Methods Appl. Mech. Eng. 2022 391 114570 10.1016/j.cma.2022.114570
    [Google Scholar]
  40. Tawfik M.A. Sagade A.A. Palma-Behnke R. Allah W.E.A. El-Shal H.M. Performance evaluation of solar cooker with tracking type bottom reflector retrofitted with a novel design of thermal storage incorporated absorber plate. J. Energy Storage 2022 51 104432 10.1016/j.est.2022.104432
    [Google Scholar]
  41. Mchergui A. Moulahi T. Zeadally S. Survey on Artificial Intelligence (AI) techniques for Vehicular Ad-hoc Networks (VANETs). Vehicular Communications 2022 34 100403 10.1016/j.vehcom.2021.100403
    [Google Scholar]
  42. Kumar Goyal R. EswaramoorthyMuthusamy Thermo-physical properties of heat storage material required for effective heat storage and heat transfer enhancement techniques for the solar cooking applications. Sustain. Energy Technol. Assess. 2023 56 103078 10.1016/j.seta.2023.103078
    [Google Scholar]
  43. Piguave B.V. Salas S.D. De Cecchis D. Romagnoli J.A. Modular framework for simulation-based multi-objective optimization of a cryogenic air separation unit. ACS Omega 2022 7 14 11696 11709 10.1021/acsomega.1c06669 35449930
    [Google Scholar]
  44. Yannibelli V. Pacini E. Monge D. Mateos C. Rodríguez G. A comparative analysis of NSGA-II and NSGA-III for autoscaling parameter sweep experiments in the cloud. Sci. Program. 2020 2020 1 17 10.1155/2020/4653204
    [Google Scholar]
  45. Swarnkar H. Jain R. Tiwari A. Vasnani H. hase change material application in solar cooking for performance enhancement through storage of thermal energy: A future demand. World J. Adv. Eng. Technol. Sci. 2024 12 1 306 330 10.30574/wjaets.2024.12.1.0239
    [Google Scholar]
/content/journals/meng/10.2174/0122127976351079241209120103
Loading
Performance Analysis of IoT-based Temperature Monitoring Box Type Solar Cooker: A Multi-objective Optimization Approach
Bentham Science Publishers ; https://doi.org/10.2174/0122127976351079241209120103
/content/journals/meng/10.2174/0122127976351079241209120103
/content/journals/meng/10.2174/0122127976351079241209120103
Loading

Data & Media loading...


  • Article Type:     Research Article
Keywords: genetic algorithm ; solar cooker performance analysis ; Internet of Things ; fitness value ; error bar ; box type solar cooker ; pareto front
This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error
Please enter a valid_number test