Embedded System for Rain Sensing Car Wiper

Year : 2024 | Volume :11 | Issue : 01 | Page : –
By

Nikhil Bagal

Abhishek Badave

Vikram Devmare

Amruta S. Mali

  1. Student Department of Electronics & Telecommunication Engineering, SKN Sinhgad College of Engineering, Pandharpur Maharashtra India
  2. Student Department of Electronics & Telecommunication Engineering, SKN Sinhgad College of Engineering, Pandharpur Maharashtra India
  3. Student Department of Electronics & Telecommunication Engineering, SKN Sinhgad College of Engineering, Pandharpur Maharashtra India
  4. Assistant Professor Department of Electronics & Telecommunication Engineering, SKN Sinhgad College of Engineering, Pandharpur Maharashtra India

Abstract

The automatic rain wiper system aims to detect rainfall and activate windshield wipers automatically, eliminating the need for manual intervention by the driver. For over a century, the driver has been the one operating the windshield wiper. The wiper should be turned on when the driver feels that driving the vehicle is difficult and that better vision is necessary. On the other hand, since the driver must concentrate solely on operating the pedals and steering wheel, assistance with wiper function is an essential ADAS feature. Developed to enhance driver focus and minimize distractions, the system employs an Arduino and rain drop sensor combination to identify rain presence and intensity. By receiving input signals from the rain drop sensor, a controller manages wiper operation accordingly. This innovation seeks to mitigate accidents caused by drivers diverting attention to adjust manual wipers while driving in rainy conditions. During inclement weather, drivers often struggle with visibility due to water droplets on the windshield, prompting them to intermittently engage manual wipers, potentially leading to accidents. Implementing a sensor-based system on the windshield detects water droplets and triggers wiper activation automatically upon detection. When the sensor no longer detects water droplets, the wipers cease operation, eliminating the need for human intervention.

Keywords: Sensors, automatic rain, weather, ADAS, arduino.

[This article belongs to Recent Trends in Sensor Research & Technology(rtsrt)]

How to cite this article: Nikhil Bagal, Abhishek Badave, Vikram Devmare, Amruta S. Mali. Embedded System for Rain Sensing Car Wiper. Recent Trends in Sensor Research & Technology. 2024; 11(01):-.
How to cite this URL: Nikhil Bagal, Abhishek Badave, Vikram Devmare, Amruta S. Mali. Embedded System for Rain Sensing Car Wiper. Recent Trends in Sensor Research & Technology. 2024; 11(01):-. Available from: https://journals.stmjournals.com/rtsrt/article=2024/view=151135

Browse Figures

References

  1. Rainy Weather Recognition from in-vehicle Camera Images for Driver Assistance by I. Ide, Y. Mekada, H. Murase, Y. Tamatsu, H. Kurihara, T. Takahashi, and T. Miyahara, in IEEE Intelligent Vehicles Symposium, 2005.
  2. KadakiaNishant, A Kothari, Mohit A Shah, Amit V Patel Vipul R: Automatic Rain Operated Wiper System in Automobile, International Journal for Scientific Research & Development Vol. 3, Issue 02, 2015
  3. AHM FazleElah and Mohammad ShafiurRehman in Intelligent Windshield for Automotive Vehicles 17th InternationalConference on Computer and Info. Technology 22-23 December 2014. International University, Dhaka Bangladesh
  4. Kurihara, T. Takahashi, I. Ide, Y. Mekada, H. Murase, Y. Tamatsu, and T. Miyahara, “Rainy Weather Recognition from in-vehicle Camera Images for Driver Assistance,” In IEEE Intelligent Vehicles Symposium, 2005, pp. 205-210
  5. Anuradha S. Joshi1, Sheeja S. Suresh, “review report on soc on various platforms for vehicles”, International Research Journal of Engineering and Technology (IRJET).
  6. Deshpande, H. S. and Karande, K. J. (2014, April). Efficient implementation of AES algorithm on FPGA. In 2014 International Conference on Communication and Signal Processing (pp. 1895-1899). IEEE.
  7. Swami, S. S. (2017, August). An efficient FPGA implementation of discrete wavelet transform for image compression. In 2017 International Conference on Energy, Communication, Data Analytics and Soft Computing (ICECDS) (pp. 3385-3389). IEEE.
  8. Mane, P. B. (2018). High speed area efficient FPGA implementation of AES algorithm. International Journal of Reconfigurable and Embedded Systems, 7(3), 157-165.
  9. Kulkarni, P. R. and; Mane, P. B. (2017). Robust invisible watermarking for image authentication. In Emerging Trends in Electrical, Communications and Information Technologies: Proceedings of ICECIT-2015(pp. 193-200). Springer Singapore.
  10. Mane, P. B. (2016). Area efficient high speed FPGA based invisible watermarking for image authentication. Indian journal of Science and Technology.
  11. Kashid, M. M., Karande, K. J. (2022, November). IoT-based environmental parameter monitoring using machine learning approach. In Proceedings of the International Conference on Cognitive and Intelligent Computing: ICCIC 2021, Volume 1 (pp. 43-51). Singapore: Springer Nature Singapore.
  12. Mane, D. P. (2017). An Efficient implementation of DWT for image compression on reconfigurable platform. International Journal of Control Theory and Applications, 10(15), 1-7.
  13. Mandwale, A. J. (2015, January). Different Approaches for Implementation of Viterbi decoder on reconfigurable platform. In 2015 International Conference on Pervasive Computing (ICPC) (pp. 1-4). IEEE.
  14. Nagane, U. P. (2021). Moving object detection and tracking using Matlab. Journal of Science and Technology, 6, 86-89.
  15. Jadhav, M. M. et al (2021). Machine learning based autonomous fire combat turret. Turkish Journal of Computer and Mathematics Education (TURCOMAT), 12(2), 2372-2381.
  16. Mane, D. P. (2019). High throughput and area efficient FPGA implementation of AES algorithm. International Journal of Engineering and Advanced Technology, 8(4).
  17. Shinde, G. N. (2021). An approach for robust digital image

watermarking using DWT‐PCA. Journal of Science and Technology, 6(1).

  1. Shinde G. (2019). A robust digital image watermarking using DWT-PCA. International Journal of Innovations in Engineering Research and Technology, 6(4), 1-7.
  2. Kalyankar, P. A., Thigale, S. P., Chavhan, P. G., and; Jadhav, M. M. (2022). Scalable face image retrieval using AESC technique. Journal of Algebraic Statistics, 13(3), 173-176.
  3. Kulkarni, P. (2015). Robust invisible digital image watermarking using discrete wavelet transform. International Journal of Engineering Research and; Technology (IJERT), 4(01), 139-141.
  4. Mane, D. P. (2018). Secure and area efficient implementation of digital image watermarking on reconfigurable platform. International Journal of Innovative Technology and Exploring Engineering, 8(2), 56-61.
  5. Deshpande, H. S. and Karande, K. J. (2015, April). Area optimized implementation of AES algorithm on FPGA. In 2015 International Conference on Communications and Signal Processing (ICCSP) (pp. 0010-0014). IEEE.
  6. Ghodake, R. G. (2016). Sensor based automatic drip irrigation system. Journal for Research, 2(02).
  7. Mane, P. B. (2019). High-Speed area-efficient implementation of AES algorithm on reconfigurable platform. Computer and Network Security, 119.
  8. Mane, P. B. (2014, October). Area optimization of cryptographic algorithm on less dense reconfigurable platform. In 2014 International Conference on Smart Structures and Systems (ICSSS) (pp. 86-89). IEEE.
  9. Takale, S. (2022). DWT-PCA Based Video Watermarking. Journal of Electronics, Computer Networking and Applied Mathematics (JECNAM) ISSN, 2799-1156.
  10. Patale, J. P., Jagadale, A. B., and; Pise, A. (2023). A Systematic survey on Estimation of Electrical Vehicle. Journal of Electronics, Computer Networking and Applied Mathematics (JECNAM) ISSN, 2799-1156.
  11. Jadhav, M. M., and; Seth, M. (2022). Painless machine learning approach to estimate blood glucose level with non-invasive devices. In Artificial Intelligence, Internet of Things (IoT) and Smart Materials for Energy Applications (pp. 83-100). CRC Press.
  12. Kondekar, R. P. (2017). Raspberry Pi based voice operated Robot. International Journal of Recent Engineering Research and Development, 2(12), 69-76.
  13. Maske, Y., Jagadale, A. B., and; Pise, A. C. (2023). Development of BIOBOT System to Assist COVID Patient and Caretakers. European Journal of Molecular and Clinical Medicine, 3472-3480.
  14. Maske, Y., Jagadale, M. A., and; Pise, M. A. (2021). Implementation of BIOBOT System for COVID Patient and Caretakers Assistant Using IOT. International Journal of Information Technology and;Amp, 30-43.
  15. Jadhav, H. M., Mulani, A., and; Jadhav, M. M. (2022). Design and development of chatbot based on reinforcement learning. Machine Learning Algorithms for Signal and Image Processing, 219-229.
  16. Gadade, B. (2022). Automatic System for Car Health Monitoring. International Journal of Innovations in Engineering Research and Technology, 57-62.
  17. Kamble, A., (2022). Google assistant based device control. Int. J. of Aquatic Science, 13(1), 550-555.
  18. Mandwale, A., and; Mulani, A. O. (2015, January). Different Approaches for

Implementation of Viterbi decoder. In IEEE International Conference on Pervasive Computing (ICPC).

  1. Mulani, A. O., Jadhav, M. M., and; Seth, M. (2022). Painless Non‐invasive blood glucose concentration level estimation using PCA and machine learning. The CRC Book entitled Artificial Intelligence, Internet of Things (IoT) and Smart Materials for Energy Applications. Internet of Things (IoT) and Smart Materials for Energy Applications.
  2. Boxey, A., Jadhav, A., Gade, P., Ghanti, P., and; Mulani, A. O. (2022). Face Recognition using Raspberry Pi. Journal of Image Processing and Intelligent Remote Sensing (JIPIRS) ISSN 2815-0953.
  3. Takale, S., and; Mulani, D. A. Video Watermarking System. International Journal for Research in Applied Science and; Engineering Technology (IJRASET), 10.
  4. Shinde, M. R. S., and; Mulani, A. O. (2015). Analysisof Biomedical Image Using Wavelet Transform. International Journal of Innovations in Engineering Research and Technology, 2(7), 1-7.
  5. Mandwale, A., and; Mulani, A. O. (2014, December). Implementation of Convolutional Encoder and; Different Approaches for Viterbi Decoder. In IEEE International Conference on Communications, Signal Processing Computing and Information technologies.
  6. Ghodake, R. G., and; Mulani, A. O. (2018). Microcontroller Based Automatic Drip Irrigation System. In Techno-Societal 2016: Proceedings of the International Conference on Advanced Technologies for Societal Applications (pp. 109-115). Springer International Publishing.
  7. Mulani, A. O., and; Mane, P. B. (2016), “Fast and Efficient VLSI Implementation of DWT for Image Compression”, International Journal of Control Theory and Applications, 9(41), pp.1006-1011.
  8. Shinde, R., and; Mulani, A. O. (2015). Analysis of Biomedical Image‖. International Journal on Recent and; Innovative trend in technology (IJRITT).
  9. Patale, J. P., Jagadale, A. B., Mulani, A. O., and; Pise, A. (2022). Python Algorithm to Estimate Range of Electrical Vehicle. Telematique, 7046-7059.
  10. Utpat, V. B., Karande, D. K., and; Mulani, D. A. Grading of Pomegranate Using Quality Analysis‖. International Journal for Research in Applied Science and; Engineering Technology (IJRASET), 10.
  11. Mulani, A. O., Jadhav, M. M., and; Seth, M. (2022). Painless Non‐invasive blood glucose concentration level estimation using PCA and machine learning. The CRC Book entitled Artificial Intelligence, Internet of Things (IoT) and Smart Materials for Energy Applications.
  12. Mandwale, A., and; Mulani, A. O. (2016). Implementation of High Speed Viterbi Decoder using FPGA. International Journal of Engineering Research and; Technology﴾
  13. Kambale, A. (2023). HOME AUTOMATION USING GOOGLE ASSISTANT. UGC care approved journal, 32(1).
  14. Sawant, R. A., and; Mulani, A. O. Automatic PCB Track Design Machine. International Journal of Innovative Science and Research Technology, 7(9).
  15. ABHANGRAO, M. R., JADHAV, M. S., GHODKE, M. P., and; MULANI, A. Design And Implementation Of 8-bit Vedic Multiplier. JournalNX, 24-26.
  16. Seth, M. (2022). Painless Machine learning approach to estimate blood glucose level of Non-Invasive device. Artificial Intelligence, Internet of Things (IoT) and Smart Materials for Energy Applications.
  17. Korake, D. M., and; Mulani, A. O. (2016). Design of Computer/Laptop Independent Data transfer system from one USB flash drive to another using ARM11 processor. International Journal of Science, Engineering and Technology Research.
  18. Mulani, A. O., Birajadar, G., Ivković, N., Salah, B., and; Darlis, A. R. (2023). Deep learning based detection of dermatological diseases using convolutional neural networks and decision trees. Treatment du Signal, 40(6), 2819-2825.
  19. Pathan, A. N., Shejal, S. A., Salgar, S. A., Harale, A. D., and; Mulani, A. O. (2022). Hand Gesture Controlled Robotic System. Int. J. of Aquatic Science, 13(1), 487-493.
  20. Altaf O. Mulani. (2024). A Comprehensive Survey on Semi-Automatic Solar-Powered Pesticide Sprayers for Farming. Journal of Energy Engineering and Thermodynamics (JEET) ISSN 2815-0945, 4(02), 21–28. https://doi.org/10.55529/jeet.42.21.28
  21. Sandeep Kedar and A. O. Mulani (2024), IoT Based Soil, Water and Air Quality Monitoring System for Pomegranate Farming, NATURALISTA CAMPANO, Vol. 28, Issue 1.
  22. Bhanudas Gadade, A O Mulani and A.D.Harale (2024). IOT Based Smart School Bus and Student Monitoring System. NATURALISTA CAMPANO, Vol. 28, Issue 1.
  23. Anil Dhanawade, A. O Mulani and Anjali. C. Pise. (2024). Smart farming using IOT based Agri BOT. NATURALISTA CAMPANO, Vol. 28, Issue 1.
  24. Shweta Sadanand Salunkhe and Dr. Altaf O. Mulani. (2024). Solar Mount Design Using High-Density Polyethylene. NATURALISTA CAMPANO, Vol. 28, Issue 1.
  25. Sarda, M., Deshpande, B., Deo, S., & Karanjkar, R. (2018). A comparative study on Maslow’s theory and Indian Ashrama system.”. International Journal of Innovative Technology and Exploring Engineering, 8(2), 48-50.
  26. Deo, S., and; Deo, S. (2019). Cybersquatting: Threat to domain name. International Journal of Innovative Technology and Exploring Engineering, 8(6), 1432-1434.
  27. Shambhavee, H. M. (2019). Cyber-Stalking: Threat to People or Bane to Technology. International Journal on Trend in Scientific Research and Development, 3(2), 350-355.
  28. Deo, S., and; Deo, D. S. (2019). Domain name and its protection in India. International Journal of Recent Technology and Engineering.
  29. Sarda, M., Deshpande, B., Deo, S., and ; Pathak, M. A. (2018). Intellectual Property And Mechanical Engineering-A Study Emphasizing The Importance Of Knowledge Of Intellectual Property Rights Amongst Mechanical Engineers. International Journal of Social Science and Economic Research, 3(12), 6591-6596.
  30. Tapan S. Kulkarni, Harsh S. Holalad, July 2012, “SemiAutomatic Rain Wiper 25 System,” International Journal of Emerging Technology and Advanced Engineering, ISSN 2250-2459, Volume 2, Issue 7.
  31. M. Z. Hashim, July 2013. “Smart Wiper Control System,” International Journal of Application or Innovation in Engineering& Management (IJAIEM), ISSN 2319 – 4847, Volume 2, Issue 7.
  32. Mali S. C., Vyavahare R. T., (2015). “An Ergonomic Evaluation of an Industrial Workstation: A Review”, International Journal of Current Engineering and Technology, vol.5, pp. 1820-1826, 2015.
  33. Mali S. C., Vyavahare R. T., (2015). “RULA Analysis of Work-related Disorders of Foundry Industry Worker Using Digital Human Modeling (DHM)”, International Research Journal of Engineering and Technology (IRJET), vol.2, Issue 5, e-ISSN: 2395-0056, p-ISSN: 2395-0072
  34. Mali S. C., Vyavahare R. T., (2020). “A Systematic Ergonomics Approach of Maintenance Workstation”, IOP Conf. Series: Materials Science and Engineering 814 (2020) 012032.
  35. V. Viswanadh, January-2015, “Design & Fabrication of Rain Operated Wiper Mechanism using Conductive Sensor Circuit,” International Journal of Engineering Research & Technology (IJERT), ISSN: 2278-0181, Vol. 4, Issue 01.
  36. Li CH, Chen KW, Lai CC, Hwang YT. Real-time rain detection and wiper control employing embedded deep learning. IEEE Transactions on Vehicular Technology. 2021 Mar 17;70(4):3256-66.

Regular Issue Subscription Original Research
Volume 11
Issue 01
Received May 5, 2024
Accepted May 15, 2024
Published May 28, 2024