Main Article Content


Purpose of Study: In the contemporary world, Internet-of-Things have become an indispensable part of our lives. The present era is of sensor-based electronic gadgets. Nowadays, more or less, every aspect of human life, from Home Automation, Healthcare, and Fitness, Agriculture, Education, Entertainment, Locomotive, Smart Farming, Smart Digital Cities, towards Industrial IoT, each one is redesigned from statistical to qualitative mechanisms. With the growing trends and technological transformations, the reality is that Internet-of-Things play a vital role. Currently, the agriculture industry is precise, and data-centered than traditional farming. Such revolutionary changes in the smart farming in the last decades are shaking the existing agriculture methods and creating new opportunities in the specific agriculture domains like crop status, insect and pest detection, and removal, irrigation, soil preparation, crop surveillance along with a range of unfolded issues and challenges. This study highlights the potential unfolded issues and challenges in the domain specific and precise selection of Internet-of-Thing based devices with supportive technologies and tools for instigating Smart Farming.

Methodology: a systematic data processing approach with literature search and screening to review, is used in this study to identify selection of suitable iot-based end-devices, tools and technologies for implementing smart farming

Main Findings: This study discussed the various IoT end-devices, tools and technologies in a well-organized manner. This study also highlights the foremost outspread challenges during selection of IoT-based resources for smart farming.

Implications: This article is beneficial to all concerned stakeholders involved in agricultural activities like farmers, agricultural institutions, professional decision makers, who are passionate for enhancing the smart farming.

Novelty/Originality of the study: Various scholars/researchers have been making efforts for smart farming by using IoT concepts in agriculture. This study make some efforts to discussed past research on IoT tools and Technology and challenges in selection of IoT devices for implementing an Iot based infrastructure for smart farming.


Communication Technology Internet-of-Things Sensor-based devices Smart Farming UAV

Article Details

How to Cite
Gupta, R., Bhatnagar, V., Kumar, G., & Singh, G. (2022). Selection of suitable IoT-based End-devices, tools, and technologies for implementing Smart Farming: Issues and Challenges. International Journal of Students’ Research in Technology & Management, 10(2), 28-35.


  1. Bhatnagar, V., Singh, G., Kumar, G and Gupta, R. (2020). Internet of Things in Smart Agriculture: Applications and Open Challenges. International Journal of Students’ Research in Technology & Management, 8(1), 11-17.
  2. Cozzolino, D., Porker, K. and Laws, M. (2015). An Overview on the Use of Infrared Sensors for in Field, Proximal and at Harvest Monitoring of Cereal Crops. Agriculture-Basel, 5, 713-722. griculture5030713
  3. Gadre, M. and Deoskar, A. (2020). Industry 4.0—digital transformation, challenges and benefits. Int. J. Future Gen. Commun. Networking, 13(2), 139–149.
  4. Kim, S., Lee, M. and Shin, C. (2018). Internet of Things-Based Strawberry Disease Prediction System for Smart Farming. Sensors, 18, 4051.
  5. Manocha, N. and Gupta, R. (2020). SIE-EVD: A Novel Satellite Image Enhancement Technique with Quality Metrices for Effective Visual Display using CBIR. International Journal of Advanced Trends in Computer Science and Engineering, 9(1.3), 470-474.
  6. Nejkovic, V., Petrovic, N., Tosic, M. and Milosevic, N. (2020). Semantic approach to RIoT autonomous robots mission coordination. Robot Auton Syst., 126, 103438.
  7. Postolache, O., Pereira, M. and Gir ao, A. (2013). Sensor network for environment monitoring: water quality case study. 4th Symposium on Environmental Instrumentation and Measurements, 30–34.
  8. Putjaika, N. (2016). A control system in an intelligent farming by using arduino technology. Student Project Conference (ICT-ISPC), Fifth ICT International IEEE.
  9. Sales, N., Remédios, O and Arsenio, A.(2015). Wireless sensor and actuator system for smart irrigation on the cloud. IEEE 2nd World Forum on Internet of Things (WF-Internet of Things), 693-698. 9/WF-IoT.2015.7389138
  10. Shuwen, W. and Changli, Z. (2015). Study on farmland irrigation remote monitoring system based on ZigBee. International Conference on Computer and Computational Sciences (ICCCS), pp. 193-197. 109/ICCACS.2015.7361348
  11. Singh, G. and Yogi, K.K. (2020). A Review on Recognition of Plant Disease using Intelligent Image Retrieval Techniques. Asian J Biol Life Sci., 9(3), 274-85.
  12. Singh, G. and Yogi, K.K. (2022a). Internet of Things-Based Devices/Robots in Agriculture 4.0. In: Karrupusamy P., Balas V.E., Shi Y. (eds) Sustainable Communication Networks and Application. Lecture Notes on Data Engineering and Communications Technologies, vol 93. Springer, Singapore.
  13. Singh, G. and Yogi, K.K. (2022b). Usage of Internet of Things Based Devices in Smart Agriculture for Monitoring the field and Pest Control. 2022 IEEE Delhi Section Conference (DELCON), pp. 1-8.
  14. Singh, G., Dubey, O. P., & Kumar, G. (2018). A solution to selective forward attack in wireless sensor network. International Journal of Students’ Research in Technology & Management, 6(4), 01-06. .18510/ijsrtm.2018.625
  15. Singh, G., Kumar, G., Bhatnagar, V., Srivastava, A., & Jyoti, K. (2019). Pollution management through internet of things: a substantial solution for society. Humanities & Social Sciences Reviews, 7(5), 1231-1237.
  16. Zujevs, A., Osadcuks, V. and Ahrendt, P. (2015). Trends in Robotic Sensor Technologies for Fruit Harvesting. Procedia Computer Science, 77, 227-233.