Sensors and smart farming using IoT: A review on potential applications in horticultural crops

Authors

  • P Hemamalini Jain University , Jain University image/svg+xml , Indian Institute of Horticultural Research image/svg+xml Author
  • M K Chandraprakash Indian Institute of Horticultural Research , Indian Institute of Horticultural Research image/svg+xml Author
  • K Suneetha Jain University , Jain University image/svg+xml Author
  • R H Laxman ICAR-Indian Institute of Horticultural Research , Indian Institute of Horticultural Research image/svg+xml Author

DOI:

https://doi.org/10.24154/jhs.v20i1.2223

Keywords:

Horticulture, internet of things, IoT, data analytics, sensors

Abstract

Horticulture farming is a subset of agriculture, contributing approximately 30% of the agricultural GDP in India. The nutritional benefits of horticultural crops such as fruits, vegetables, and mushrooms play an important role in daily life. With the ever-increasing demand for food, the horticultural industry faces new challenges that require innovative and sustainable solutions. This has led to a significant shift towards technology-driven solutions to address the challenges of a growing population in a sustainable way. The Internet of Things (IoT), a promising technology in smart farming, greatly helps in real-time monitoring of plant growth status and facilitates faster decisions under challenging circumstances. Smart farming in horticultural crops relies on a range of components including sensors, actuators, microcontrollers, and cloud storage for the effective implementation of IoT. These components work together to collect and store data, which can be utilized to optimize the allocation of input resources. This review discusses how components of smart farming can improve resource management, crop yields, and the quality of production of horticultural crops, along with its applications and development in this area.

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Author Biographies

  • P Hemamalini, Jain University, Jain University, Indian Institute of Horticultural Research

    Jain University (Deemed-to-be-University), Bengaluru - 560078, India

    ICAR-Indian Institute of Horticultural Research, Bengaluru - 560089, India

  • M K Chandraprakash, Indian Institute of Horticultural Research, Indian Institute of Horticultural Research

    ICAR-Indian Institute of Horticultural Research, Bengaluru - 560089, India

  • K Suneetha, Jain University, Jain University

    Jain University

References

Aarthi, R., Sivakumar, D., & Mariappan, V. (2023). Smart soil property analysis using IoT: A case study implementation in backyard gardening. Procedia Computer Science, 218, 2842–2851. https://doi.org/10.1016/j.procs.2023.01.255

Abdelouhahid, R. A., Debauche, O., Mahmoudi, S., Marzak, A., Manneback, P., & Lebeau, F. (2020). Open phytotron: A new IoT device for home gardening. In 2020 5th International Conference on Cloud Computing and Artificial Intelligence: Technologies and Applications (CloudTech) (pp. 1–8). IEEE. https://doi.org/10.1109/cloudtech49835.2020.9365892

Al Rafi, F., Kowanda, A., Salahuddin, N. S., & Saptriani, T. (2018). Design of orchid monitoring system based on IoT. In 2018 Third International Conference on Informatics and Computing (ICIC) (pp. 1–6). IEEE. https://doi.org/10.1109/IAC.2018.8780419

Al-Zahrani, S., & Al-Baity, H. H. (2019). Smart irrigation control system using Internet of Things: An empirical study in Kingdom of Saudi Arabia. An International Peer Reviewed Open Access Journal for Rapid Publication, 539. http://dx.doi.org/10.21786/bbrc/12.2/42

Aziz, M. H., Saptiani, P., Iryanti, M., & Aminudin, A. (2019). Design of carbon dioxide level measures on peat soil with MG 811 sensor. Journal of Physics: Conference Series, 1280(2), 022061. https://doi.org/10.1088/1742-6596/1280/2/022061

Bardhan, S., Jenamani, M., & Routray, A. (2022). Improving IoT sensor data quality using Kalman filter: The case of cold chain monitoring for Indian mangoes. In 2022 IEEE 7th International Conference for Convergence in Technology (I2CT) (pp. 1–8). IEEE. https://doi.org/10.1109/I2CT54291.2022.9825458

Bicans, J., Kviesis, K., & Avotins, A. (2019). IoT camera-based approach to capture and process SI-NDVI sensor data for industrial tomato greenhouse. In 2019 IEEE 7th Workshop on Advances in Information, Electronic and Electrical Engineering (AIEEE) (pp. 1–6). IEEE. https://doi.org/10.1109/AIEEE48629.2019.8977127

Biqing, L., Yongfa, L., Miao, T., & Shiyong, Z. (2018). Design and implementation of sugarcane growth monitoring system based on RFID and ZigBee. International Journal of Online Engineering, 14(3). https://doi.org/10.3991/ijoe.v14i03.8413

Chen, X., Su, Y., Li, Y., Han, L., Liao, J., & Yang, S. (2014). Retrieving China’s surface soil moisture and land surface temperature using AMSR-E brightness temperatures. Remote Sensing Letters, 5(7), 662–671. https://doi.org/10.1080/2150704X.2014.960610

Choudhury, S. B., Jain, P., Kallamkuth, S., Ramanath, S., Bhatt, P. V., Sarangi, S., & Srinivasu, P. (2019). Precision crop monitoring with affordable IoT: Experiences with okra. In 2019 Global IoT Summit (GIoTS) (pp. 1–6). IEEE. https://doi.org/10.1109/GIOTS.2019.8766417

Choudhury, S., Singh, R., Gehlot, A., Kuchhal, P., Akram, S. V., Priyadarshi, N., & Khan, B. (2022). Agriculture field automation and digitization using Internet of Things and machine learning. Journal of Sensors. https://doi.org/10.1155/2022/9042382

Datta, S., Taghvaeian, S., Ochsner, T. E., Moriasi, D., Gowda, P., & Steiner, J. L. (2018). Performance assessment of five different soil moisture sensors under irrigated field conditions in Oklahoma. Sensors, 18(11), 3786.

Deliana, M., Mutiawani, V., & Dawood, R. (2022). Monitoring system 4.0 on horticultural plantation land based on the Internet of Things. In International Conference on Electrical Engineering and Informatics (ICELTICs) (pp. 101–106). IEEE. https://doi.org/10.1109/ICELTICS56128.2022.9932104

Dewi, C., & Chen, R. C. (2019). Decision-making based on IoT data collection for precision agriculture. In Asian Conference on Intelligent Information and Database Systems (pp. 31–42). Springer. https://doi.org/10.1007/978-3-030-14132-5_3

Elsherbiny, O., Zhou, L., He, Y., & Qiu, Z. (2022). A novel hybrid deep network for diagnosing water status in wheat crop using IoT-based multimodal data. Computers and Electronics in Agriculture, 203, 107453. https://doi.org/10.1016/j.compag.2022.107453

Gogoi, S., Saikia, B., Boruah, P., & Khamari, B. (2022). Internet of Things (IoT) based insect pest detection and management. In S. Sanjay-Swami (Ed.), Advancing Innovations in Sustainable Agriculture (Vol. 1, pp. 73–80). Vital Biotech Publication.

Hasyer, M. A., Khalid, A. M., Neranjan, N., Belayan, J., Metali, F., Yassin, H., & Bakar, M. S. A. (2023). IoT-powered pest management system for chili plants: Analyzing the effects of various light spectra towards pest and plant health. IEEE Asia-Pacific Conference on Computer Science and Data Engineering, 1–6. https://doi.org/10.1109/CSDE59766.2023.10487659

Høye, T. T., Ärje, J., Bjerge, K., Hansen, O. L., Iosifidis, A., Leese, F., & Raitoharju, J. (2021). Deep learning and computer vision will transform entomology. Proceedings of the National Academy of Sciences, 118(2). https://doi.org/10.1073/pnas.2002545117

Kaburuan, E. R., & Jayadi, R. (2019). A design of IoT-based monitoring system for intelligent indoor micro-climate horticulture farming in Indonesia. Procedia Computer Science, 157, 459–464. https://doi.org/10.1016/j.procs.2019.09.001

Keates, O. (2023). Actionable insights for horticulture supply chains through advanced IoT analytics. Procedia Computer Science, 217, 1631–1640. https://doi.org/10.1016/j.procs.2022.12.363

Kumkhet, B., Rakluea, P., Sangmahamad, P., Pirajnanchai, V., Pechrkool, T., & Sutham, T. (2022). IoT-based automatic brightness and soil moisture control system for Gerbera smart greenhouse. In 2022 International Electrical Engineering Congress (iEECON) (pp. 1–4). IEEE. https://doi.org/10.1109/IEECON53204.2022.9741578

Laxman, R. H., Hemamalini, P., Namratha, M. R., Bhatt, R. M., & Sadashiva, A. T. (2022). Phenotyping deficit moisture stress tolerance in tomato using image-derived digital features. International Journal of Bio-resource and Stress Management, 13(4), 339–347. https://doi.org/10.23910/1.2022.2544

Laxman, R. H., Hemamalini, P., Bhatt, R. M., & Sadashiva, A. T. (2018). Non-invasive quantification of tomato (Solanum lycopersicum L.) plant biomass through digital imaging using phenomics platform. Indian Journal of Plant Physiology, 23, 369–375. https://doi.org/10.1007/s40502-018-0374-8

Marcos, L., & Mai, K. V. (2020). Light spectra optimization in indoor plant growth for Internet of Things. In 2020 IEEE International IoT, Electronics and Mechatronics Conference (IEMTRONICS) (pp. 1–6). IEEE. https://doi.org/10.1109/IEMTRONICS51293.2020.9216421

Mittal, A., Sarangi, S., Ramanath, S., Bhatt, P. V., Sharma, R., & Srinivasu, P. (2018). IoT-based precision monitoring of horticultural crops: A case study on cabbage and capsicum. In IEEE Global Humanitarian Technology Conference (GHTC) (pp. 1–7). IEEE. https://doi.org/10.1109/GHTC.2018.8601908

Muangprathub, J., Boonnam, N., Kajornkasirat, S., Lekbangpong, N., Wanichsombat, A., & Nillaor, P. (2019). IoT and agriculture data analysis for smart farm. Computers and Electronics in Agriculture, 156, 467–474. https://doi.org/10.1016/j.compag.2018.12.011

Nayagam, M. G., Vijayalakshmi, B., Somasundaram, K., Mukunthan, M. A., Yogaraja, C. A., & Partheeban, P. (2023). Control of pests and diseases in plants using IoT technology. Measurement: Sensors, 26, 100713.

Namgyel, T., Siyang, S., Khunarak, C., Pobkrut, T., Norbu, J., Chaiyasit, T., & Kerdcharoen, T. (2018). IoT-based hydroponic system with supplementary LED light for smart home farming of lettuce. In 2018 15th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (pp. 221–224). https://doi.org/10.1109/ECTICON.2018.8619983

Palconit, M. G. B., Macachor, E. B., Notarte, M. P., Molejon, W. L., Visitacion, A. Z., Rosales, M. A., & Dadios, E. P. (2020). IoT-based precision irrigation system for eggplant and tomato. In 9th International Symposium on Computational Intelligence and Industrial Applications (pp. 0–6).

Postolache, S., Sebastião, P., Viegas, V., Postolache, O., & Cercas, F. (2022). IoT-based systems for soil nutrients assessment in horticulture. Sensors, 23(1), 403. https://doi.org/10.3390/s23010403

Pramanik, M., Khanna, M., Singh, M., Singh, D. K., Sudhishri, S., Bhatia, A., & Ranjan, R. (2021). Automation of soil moisture sensor-based basin irrigation system. Smart Agricultural Technology, 2, 100032. https://doi.org/10.1016/j.atech.2021.100032

Rahman, H., Faruq, M. O., Hai, T. B. A., Rahman, W., Hossain, M. M., Hasan, M., & Azad, M. M. (2022). IoT-enabled mushroom farm automation with machine learning to classify toxic mushrooms in Bangladesh. Journal of Agriculture and Food Research, 100267. https://doi.org/10.1016/j.jafr.2021.100267

Ren, L., Zhai, X., Yang, Y., & Xu, J. (2020). Design of horticultural wireless intelligent maintenance system based on STM32 and Android. IOP Conference Series: Earth and Environmental Science, 474(3), 032016. https://doi.org/10.1088/1755-1315/474/3/032016

Reynolds, D., Ball, J., Bauer, A., Davey, R., Griffiths, S., & Zhou, J. (2019). CropSight: A scalable and open-source information management system for distributed plant phenotyping and IoT-based crop management. GigaScience, 8(3), giz009. https://doi.org/10.1093/gigascience/giz009

Saranya, K., Dharini, P. U., Darshni, P. U., & Monisha, S. (2019). IoT-based pest controlling system for smart agriculture. In International Conference on Communication and Electronics Systems (ICCES) (pp. 1548–1552). https://doi.org/10.1109/ICCES45898.2019.9002046

Sengupta, A., Mukherjee, A., Das, A., & De, D. (2021). GrowFruit: An IoT-based radial growth rate monitoring device for fruit. IEEE Consumer Electronics Magazine, 11(3), 38–43. https://doi.org/10.1109/MCE.2021.3119276

Sengupta, A., Mukherjee, A., Das, A., & De, D. (2022). AgriStick: An IoT-enabled agricultural appliance to measure growth of jackfruit using 2-axis joystick. IEEE Instrumentation & Measurement Magazine, 25(3), 58–62. https://doi.org/10.1109/MIM.2022.9759351

Shakir, A. A., Hakim, F., Rasheduzzaman, M., Chakraborty, S., Ahmed, T. U., & Hossain, S. (2019). Design and implementation of SENSEPACK: An IoT-based mushroom cultivation monitoring system. In 2019 International Conference on Electrical, Computer and Communication Engineering (pp. 1–6). IEEE. https://doi.org/10.1109/ECACE.2019.8679183

Smolka, M., Puchberger-Enengl, D., Bipoun, M., Klasa, A., Kiczkajlo, M., Oemiechowski, W., & Vellekoop, M. J. (2017). A mobile lab-on-a-chip device for on-site soil nutrient analysis. Precision Agriculture, 18(2), 152–168. https://doi.org/10.1007/s11119-016-9452-y

Soler-Méndez, M., Parras-Burgos, D., Benouna-Bennouna, R., & Molina-Martínez, J. M. (2022). Agroclimatic evolution web application as a powerful solution for managing climate data. Scientific Reports, 12(1), 1–13. https://doi.org/10.1038/s41598-022-10316-7

Sudana, D., & Eman, D. (2019). IoT-based hydroponic system using drip non-circulation system for paprika. In International Conference of Artificial Intelligence and Information Technology (pp. 124–128). https://doi.org/10.1109/ICAIIT.2019.8834581

Taşkın, D., & Taşkın, C. (2018). Developing a Bluetooth low-energy sensor node for greenhouse precision agriculture as an Internet of Things application. Advances in Science and Technology: Research Journal, 12(4). https://doi.org/10.12913/22998624/100342

Wan, X. F., Zheng, T., Cui, J., Zhang, F., Ma, Z. Q., & Yang, Y. (2019). Near-field communication-based agricultural management service systems for family farms. Sensors, 19(20), 4406. https://doi.org/10.3390/s19204406

Xiao, X., Fu, Y., Yang, Y., Nikitina, M. A., & Zhang, X. (2022). Battery-free wireless moisture sensor system for fruit monitoring. Results in Engineering, 14, 100420. https://doi.org/10.1016/j.rineng.2022.100420

Zhang, J., Liu, P., Xue, W., & Rui, Z. (2018). Farmland intelligent information collection system based on NB-IoT. In Cloud Computing and Security: 4th International Conference, Haikou, China, June 8–10, 2018, Revised Selected Papers, Part V (pp. 331–343). Springer. https://doi.org/10.1007/978-3-030-00018-9_30

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Published

30-06-2025

Data Availability Statement

NA

Issue

Section

Review

How to Cite

Hemamalini, P., Chandraprakash, M. K., Suneetha, K., & Laxman, R. H. (2025). Sensors and smart farming using IoT: A review on potential applications in horticultural crops. Journal of Horticultural Sciences, 20(1). https://doi.org/10.24154/jhs.v20i1.2223

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