It is proposing an IoT-based weather monitoring system. This will monitor, in real-time, the critical environmental parameters aid for farming. Soil moisture, temperature, humidity, and rainfall will be measured parameters that help optimize agricultural practices and perfect the use of water. The IoT technology will, therefore, include a microcontroller such as NodeMCU that tracks soil moisture levels and automates irrigation. If the soil moisture falls below 50%, then the programming will start the motor irrigating the fields. Both moisture and motor states are displayed on LCD and sent to the Blynk app, so through this application, farmers can check the status remotely through their smartphone. In addition, it continuously monitors real-time temperatures and humidity levels. The Internet of Things (IoT) has significantly transformed farming operations by enhancing data collection and monitoring processes. Sensors placed in remote field locations can gather real-time environmental data, allowing farmers to make immediate decisions, such as whether to irrigate crops or protect them from unexpected rainfall. With IoT integration, tasks like irrigation can be automated, reducing the need for manual intervention and increasing efficiency. Additionally, IoT systems can store data over time, providing insights into long-term weather patterns. This information helps optimize farmland management, ultimately leading to higher crop yields. Continuous updating of data is provided in the Blynk app for ease of access. It uses one rain sensor module connected with Arduino Uno through a GSM module to send real-time signals whenever there is the presence of rainfall and thus affords an initial response to any change in weather. So, it supports efficient irrigation and guards’ crops from unwanted rainfalls. Therefore, the whole aim of this initiative is to ensure that agriculture remains sustainable and such appropriate weather data is available at the right time to the farmers. This is the internet of things: an inexpensive and user-friendly solution to augment productivity in agriculture in combination with resource management; the project should, as such, demonstrate how using the IoT application introduces smart agricultural tools for water usage reduction and improvement in crop management decisions.

Keywords:IoT, weather monitoring, agriculture, soil moisture, rain detection, NodeMCU, Arduino, real-time data, Blynk application, GSM module.

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1. Kazi KS. AI-Powered IoT (AI IoT) for Decision-Making in Smart Agriculture: KSK Approach for Smart Agriculture. In Enhancing Automated Decision-Making Through AI 2025 (pp. 67-96). IGI Global Scientific Publishing.
2. Sapna VK, Sachan K, Singh A. IoT Innovations Revolutionizing Agricultural Practices for Sustainability. Journal of Diversity Studies. 2024.
3. Dhanaraju M, Chenniappan P, Ramalingam K, Pazhanivelan S, Kaliaperumal R. Smart farming: Internet of Things (IoT)-based sustainable agriculture. Agriculture. 2022 Oct 21;12(10):1745.
4. Esposito M, Palma L, Belli A, Sabbatini L, Pierleoni P. Recent advances in internet of things solutions for early warning systems: A review. Sensors. 2022 Mar 9;22(6):2124.
5. Okai GE, Minta FK, Osman AM, Essilfie A. IoT-based Weather Monitoring System for Ghanaian Farmers. International Journal of Computer Applications.;975:8887.
6. Sawant RA, Mulani AO. Automatic PCB Track Design Machine. International Journal of Innovative Science and Research Technology. 2022;7(9).
7. ABHANGRAO MR, JADHAV MS, GHODKE MP, MULANI A. Design And Implementation Of 8-bit Vedic Multiplier. International Journal of Research Publications in Engineering and Technology (ISSN No: 2454-7875). 2017 Mar.
8. Korake DM, Mulani AO. 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. 2016.
9. Kolekar SD, Walekar VB, Patil PS, Mulani AO, Harale AD. Password Based Door Lock System. Int. J. of Aquatic Science. 2022 Jan 1;13(1):494-501.
10. Gadade B, Mulani AO, Harale AD. Iot based smart school bus and student monitoring system. Naturalista Campano. 2024;28(1):730-7.
11. Seth M. 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. 2022.
12. Mulani DA. A Comprehensive Survey on Semi-Automatic Solar-Powered Pesticide Sprayers for Farming. Journal of Energy Engineering and Thermodynamics (JEET) ISSN. 2024:2815-0945.
13. Kolhe VA, Pawar SY, Gohery S, Mulani AO, Sundari MS, Kiradoo G, Sivaprakash M, Sunil J. Computational and experimental analyses of pressure drop in curved tube structural sections of Coriolis mass flow metre for laminar flow region. Ships and Offshore Structures. 2024 Nov 1;19(11):1974-83.
14. Salunkhe DS, Mulani DA. Solar Mount Design Using High-Density Polyethylene. NATURALISTA CAMPANO. 2024;28(1).
15. Birajadar GB, Mulani AO, Khalaf OI, Farhah N, Gawande PG, Kinage K, Hamad AA. Epilepsy Identification using Hybrid CoPrO-DCNN Classifier. Int. J. Com. Dig. Sys. 2024 Aug;16(1).
16. Godase MV, Mulani A, Ghodak MR, Birajadar MG, Takale MS, Kolte M. A MapReduce and Kalman Filter based Secure IIoT Environment in Hadoop.
17. Liyakat KK. IoT-Based Weather Information Prototype Using WeMos. Journal of Control and Instrumentation Engineering. 2023;9(1):10-22.
18. Kulkarni TM, Mulani AO. Deep Learning Based Face-Mask Detection: An Approach to Reduce Pandemic Spreads in Human Healthcare.
19. Pol RS, Bhalerao MV, Mulani AO. A real time IoT based System Prediction and Monitoring of Landslides.
20. Gadade B, Mulani AO, Harale AD. Iot based smart school bus and student monitoring system. Naturalista Campano. 2024;28(1):730-7.
21. Shinde MR, Mulani AO. Analysisof Biomedical Image Using Wavelet Transform. International Journal of Innovations in Engineering Research and Technology. 2015;2(7):1-7.
22. Kedar MS, Mulani A. IoT Based Soil, Water and Air Quality Monitoring System for Pomegranate Farming.
23. Negi A, Kumar K. Face mask detection in real‐time video stream using deep learning. Computational intelligence and healthcare informatics. 2021 Oct 7:255-68.
24. Tamilselvi V, Sribalaji S, Vigneshwaran P, Vinu P, GeethaRamani J. IoT based health monitoring system. In2020 6th International conference on advanced computing and communication systems (ICACCS) 2020 Mar 6 (pp. 386-389). IEEE.
25. Mulani AO, Bang AV, Birajadar GB, Deshmukh AB, Jadhav HM, Liyakat KK. IoT Based Air, Water, and Soil Monitoring System for Pomegranate Farming. Annals of Agri-Bio Research. 2024;29(2):71-86.
26. Thigale SP, Jadhav HM, Mulani AO, Birajadar GB, Nagrale M, Sardey MP. Internet of things and robotics in transforming healthcare services. Afr J Biol Sci (S Afr). 2024;6(6):1567-75.
27. Kulkarni PR, Mulani AO, Mane PB. Robust invisible watermarking for image authentication. InEmerging Trends in Electrical, Communications and Information Technologies: Proceedings of ICECIT-2015 2017 (pp. 193-200). Springer Singapore. Aiwale S, Kolte MT, Harpale V, Bendre V, Khurge D, Bhandari S, Kadam S, Mulani AO. Non-invasive Anemia Detection and Prediagnosis. Journal of Pharmacology and Pharmacotherapeutics. 2024 Dec;15(4):408-16.

It is proposing an IoT-based weather monitoring system. This will monitor, in real-time, the critical environmental parameters aid for farming. Soil moisture, temperature, humidity, and rainfall will be measured parameters that help optimize agricultural practices and perfect the use of water. The IoT technology will, therefore, include a microcontroller such as NodeMCU that tracks soil moisture levels and automates irrigation. If the soil moisture falls below 50%, then the programming will start the motor irrigating the fields. Both moisture and motor states are displayed on LCD and sent to the Blynk app, so through this application, farmers can check the status remotely through their smartphone. In addition, it continuously monitors real-time temperatures and humidity levels. The Internet of Things (IoT) has significantly transformed farming operations by enhancing data collection and monitoring processes. Sensors placed in remote field locations can gather real-time environmental data, allowing farmers to make immediate decisions, such as whether to irrigate crops or protect them from unexpected rainfall. With IoT integration, tasks like irrigation can be automated, reducing the need for manual intervention and increasing efficiency. Additionally, IoT systems can store data over time, providing insights into long-term weather patterns. This information helps optimize farmland management, ultimately leading to higher crop yields. Continuous updating of data is provided in the Blynk app for ease of access. It uses one rain sensor module connected with Arduino Uno through a GSM module to send real-time signals whenever there is the presence of rainfall and thus affords an initial response to any change in weather. So, it supports efficient irrigation and guards’ crops from unwanted rainfalls. Therefore, the whole aim of this initiative is to ensure that agriculture remains sustainable and such appropriate weather data is available at the right time to the farmers. This is the internet of things: an inexpensive and user-friendly solution to augment productivity in agriculture in combination with resource management; the project should, as such, demonstrate how using the IoT application introduces smart agricultural tools for water usage reduction and improvement in crop management decisions.

Keywords:IoT, weather monitoring, agriculture, soil moisture, rain detection, NodeMCU, Arduino, real-time data, Blynk application, GSM module.

🔒 This is a subscription article

Full text is available to subscribers and institutional members. Please choose an option below to access it.

1. Kazi KS. AI-Powered IoT (AI IoT) for Decision-Making in Smart Agriculture: KSK Approach for Smart Agriculture. In Enhancing Automated Decision-Making Through AI 2025 (pp. 67-96). IGI Global Scientific Publishing.
2. Sapna VK, Sachan K, Singh A. IoT Innovations Revolutionizing Agricultural Practices for Sustainability. Journal of Diversity Studies. 2024.
3. Dhanaraju M, Chenniappan P, Ramalingam K, Pazhanivelan S, Kaliaperumal R. Smart farming: Internet of Things (IoT)-based sustainable agriculture. Agriculture. 2022 Oct 21;12(10):1745.
4. Esposito M, Palma L, Belli A, Sabbatini L, Pierleoni P. Recent advances in internet of things solutions for early warning systems: A review. Sensors. 2022 Mar 9;22(6):2124.
5. Okai GE, Minta FK, Osman AM, Essilfie A. IoT-based Weather Monitoring System for Ghanaian Farmers. International Journal of Computer Applications.;975:8887.
6. Sawant RA, Mulani AO. Automatic PCB Track Design Machine. International Journal of Innovative Science and Research Technology. 2022;7(9).
7. ABHANGRAO MR, JADHAV MS, GHODKE MP, MULANI A. Design And Implementation Of 8-bit Vedic Multiplier. International Journal of Research Publications in Engineering and Technology (ISSN No: 2454-7875). 2017 Mar.
8. Korake DM, Mulani AO. 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. 2016.
9. Kolekar SD, Walekar VB, Patil PS, Mulani AO, Harale AD. Password Based Door Lock System. Int. J. of Aquatic Science. 2022 Jan 1;13(1):494-501.
10. Gadade B, Mulani AO, Harale AD. Iot based smart school bus and student monitoring system. Naturalista Campano. 2024;28(1):730-7.
11. Seth M. 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. 2022.
12. Mulani DA. A Comprehensive Survey on Semi-Automatic Solar-Powered Pesticide Sprayers for Farming. Journal of Energy Engineering and Thermodynamics (JEET) ISSN. 2024:2815-0945.
13. Kolhe VA, Pawar SY, Gohery S, Mulani AO, Sundari MS, Kiradoo G, Sivaprakash M, Sunil J. Computational and experimental analyses of pressure drop in curved tube structural sections of Coriolis mass flow metre for laminar flow region. Ships and Offshore Structures. 2024 Nov 1;19(11):1974-83.
14. Salunkhe DS, Mulani DA. Solar Mount Design Using High-Density Polyethylene. NATURALISTA CAMPANO. 2024;28(1).
15. Birajadar GB, Mulani AO, Khalaf OI, Farhah N, Gawande PG, Kinage K, Hamad AA. Epilepsy Identification using Hybrid CoPrO-DCNN Classifier. Int. J. Com. Dig. Sys. 2024 Aug;16(1).
16. Godase MV, Mulani A, Ghodak MR, Birajadar MG, Takale MS, Kolte M. A MapReduce and Kalman Filter based Secure IIoT Environment in Hadoop.
17. Liyakat KK. IoT-Based Weather Information Prototype Using WeMos. Journal of Control and Instrumentation Engineering. 2023;9(1):10-22.
18. Kulkarni TM, Mulani AO. Deep Learning Based Face-Mask Detection: An Approach to Reduce Pandemic Spreads in Human Healthcare.
19. Pol RS, Bhalerao MV, Mulani AO. A real time IoT based System Prediction and Monitoring of Landslides.
20. Gadade B, Mulani AO, Harale AD. Iot based smart school bus and student monitoring system. Naturalista Campano. 2024;28(1):730-7.
21. Shinde MR, Mulani AO. Analysisof Biomedical Image Using Wavelet Transform. International Journal of Innovations in Engineering Research and Technology. 2015;2(7):1-7.
22. Kedar MS, Mulani A. IoT Based Soil, Water and Air Quality Monitoring System for Pomegranate Farming.
23. Negi A, Kumar K. Face mask detection in real‐time video stream using deep learning. Computational intelligence and healthcare informatics. 2021 Oct 7:255-68.
24. Tamilselvi V, Sribalaji S, Vigneshwaran P, Vinu P, GeethaRamani J. IoT based health monitoring system. In2020 6th International conference on advanced computing and communication systems (ICACCS) 2020 Mar 6 (pp. 386-389). IEEE.
25. Mulani AO, Bang AV, Birajadar GB, Deshmukh AB, Jadhav HM, Liyakat KK. IoT Based Air, Water, and Soil Monitoring System for Pomegranate Farming. Annals of Agri-Bio Research. 2024;29(2):71-86.
26. Thigale SP, Jadhav HM, Mulani AO, Birajadar GB, Nagrale M, Sardey MP. Internet of things and robotics in transforming healthcare services. Afr J Biol Sci (S Afr). 2024;6(6):1567-75.
27. Kulkarni PR, Mulani AO, Mane PB. Robust invisible watermarking for image authentication. InEmerging Trends in Electrical, Communications and Information Technologies: Proceedings of ICECIT-2015 2017 (pp. 193-200). Springer Singapore. Aiwale S, Kolte MT, Harpale V, Bendre V, Khurge D, Bhandari S, Kadam S, Mulani AO. Non-invasive Anemia Detection and Prediagnosis. Journal of Pharmacology and Pharmacotherapeutics. 2024 Dec;15(4):408-16.