Modified Context Aware Middleware Architecture for Precision Agriculture

Main Article Content

D J Anusha
R Anandan
P. Venkata Krishna


The opportunities for researchers are enhanced with the progression in the technology of communication and computing. The ease in life of many people like farmers, educators, administers, managers, etc., is increased with more inventions of the researchers using this new technology. The progressive technology for data management is providing more amount of information. However, is the user able to access the needed information when required? This question rises to the more questions like, how to identify whether the information is as per the requirement? Whether a user is authorized or not? The answer for all the questions is to make the support aware of the context. Therefore, the present technology needs to be modified to make the system aware about the context. The process of demonstrating the services based on the context using Wireless Sensor Networks (WSN) with the help of illustration on mango crop is emphasized in this paper. There are many serious problems like unsuitable fertilizer use, wrong selection of crops in wrong seasons, water waste, poor publicizing in the case of farming. These problems are addressed using the ubiquitous context aware middleware architecture for precision agriculture in mango crop.

Article Details

How to Cite
Anusha, D. J. ., Anandan, R. ., & Krishna, P. V. . (2022). Modified Context Aware Middleware Architecture for Precision Agriculture. International Journal on Recent and Innovation Trends in Computing and Communication, 10(7), 112–120.


. W. Zhang, G. Kantor, and S. Singh, “Integrated Wireless Sensor/Actuator Networks in an Agricultural Application,” in Proc. 2nd ACM Int’l Conf. Embedded Networked Sensor Systems (SENSYS 04), ACM Press, 2004, pp. 317.

. Tapankumar Basu, Vijaya R. Thool, Ravindra C. Thool, and Anjali C. Birajdar, “Computer Based Drip Irrigation Control System with Remote Data Acquisition System,” in Proc. 4th World Congress Conf. Computers in Agriculture and Natural Resources, USA, July 2006.

. Y. Kim, R.G. Evans, and W. Iversen, “Remote Sensing and Control of Irrigation System using a Distributed Wireless Sensor Network,” IEEE Trans. Instrumentation and Measurement, 2007.

. A. Baggio, “Wireless Sensor Networks in Precision Agriculture,” in Proc. ACM Workshop Real-World Wireless Sensor Networks, 2005.

. Pawan Kumar Tiwari, Mukesh Kumar Yadav, R. K. G. A. . (2022). Design Simulation and Review of Solar PV Power Forecasting Using Computing Techniques. International Journal on Recent Technologies in Mechanical and Electrical Engineering, 9(5), 18–27.

. T. Wark, P. Corke, P. Sikka, L. Klingbeil, Y Guo, C. Crossman, P. Valencia, and D. Swain, “Transforming Agriculture through Pervasive Wireless Sensor Networks,” IEEE Pervasive Computing, pp. 50–57, April-June 2007.

. Lim, H., Y. Teo, P. Mukherjee, V. Lam, W. Wong, and S. See, 2005. Sensor Grid: Integration of Wireless Sensor Networks and the Grid. In the Proceedings of the IEEE Conference on Local Computer Networks, pp:91-99.

. A. Rehman, “A review of wireless sensors and networks applications in agriculture”, Comput. Stand. Interfaces, doi:10.1016/j.csi.2011.03.004, 2011.

. Gupta, D. J. . (2022). A Study on Various Cloud Computing Technologies, Implementation Process, Categories and Application Use in Organisation. International Journal on Future Revolution in Computer Science &Amp; Communication Engineering, 8(1), 09–12.

. J. Hwang, C. Shin and H. Yoe “Study on an Agricultural Environment Monitoring Server system using the Wireless sensor network” Sensors 2010, 10, 11189-11211; doi:10.3390/s101211189.

. M. Mizoguchi, T. Ito and S. Mitsuishi “Ubiquitous monitoring of agricultural fields in Asia using wireless sensor network” 19th World congress of Soil Science, August 2010.

. J. Hwang and H. Yoe “Study on the Context aware Middleware for ubiquitous greenhouses using Wireless sensor networks” Sensors. 2011, 11, 4539-4561, 2011.

. Krishna, P. V., Sivanesan, S., Misra, S., & Obaidat, M. S. (2015, July). Learning automaton based context oriented middleware architecture for precision agriculture. In 2015 International Conference on Computer, Information and Telecommunication Systems (CITS) (pp. 1-5). IEEE.

. Ayaz, M., Ammad-Uddin, M., Sharif, Z., Mansour, A., & Aggoune, E. H. M. (2019). Internet-of-Things (IoT)-based smart agriculture: Toward making the fields talk. IEEE Access, 7, 129551-129583.

. M. . Parhi, A. . Roul, B. Ghosh, and A. Pati, “IOATS: an Intelligent Online Attendance Tracking System based on Facial Recognition and Edge Computing”, Int J Intell Syst Appl Eng, vol. 10, no. 2, pp. 252–259, May 2022.

. Farooq, M. S., Riaz, S., Abid, A., Abid, K., & Naeem, M. A. (2019). A Survey on the Role of IoT in Agriculture for the Implementation of Smart Farming. IEEE Access, 7, 156237-156271.

. Corista, P., Ferreira, D., Gião, J., Sarraipa, J., & Gonçalves, R. J. (2018, June). An IoT agriculture system using FIWARE. In 2018 IEEE International Conference on Engineering, Technology and Innovation (ICE/ITMC) (pp. 1-6). IEEE.

. Davcev, D., Mitreski, K., Trajkovic, S., Nikolovski, V., & Koteli, N. (2018, June). IoT agriculture system based on LoRaWAN. In 2018 14th IEEE International Workshop on Factory Communication Systems (WFCS) (pp. 1-4). IEEE.

. Elijah, O., Rahman, T. A., Orikumhi, I., Leow, C. Y., & Hindia, M. N. (2018). An overview of Internet of Things (IoT) and data analytics in agriculture: Benefits and challenges. IEEE Internet of Things Journal, 5(5), 3758-3773.

. Ahmed, N., De, D., & Hussain, I. (2018). Internet of Things (IoT) for smart precision agriculture and farming in rural areas. IEEE Internet of Things Journal, 5(6), 4890-4899.

. Alhasnawi, B. N., Jasim, B. H., & Issa, B. A. (2020). Internet of Things (IoT) for Smart Precision Agriculture. Iraqi Journal for Electrical and Electronic Engineering, 16(1).

. Khanna, A., & Kaur, S. (2019). Evolution of Internet of Things (IoT) and its significant impact in the field of Precision Agriculture. Computers and electronics in agriculture, 157, 218-231.

. Vanitha, D. D. . (2022). Comparative Analysis of Power switches MOFET and IGBT Used in Power Applications. International Journal on Recent Technologies in Mechanical and Electrical Engineering, 9(5), 01–09.

. Jasuja, V., & Singh, R. K. (2019). Enhanced MBFD Algorithm to Minimize Energy Consumption in Cloud. International Journal of Computer Engineering in ResearchTrends, 6(2). pp: 266-271, February-2019

. Associating Social Media to e-Merchandise - A Cold Start Commodity Recommendation

. Begum, M., Rao, G., & Tech, P. (2017). Associating Social Media to e-Merchandise -A Cold Start Commodity Recommendation. International Journal of Computer Engineering in Research Trends, 4(10), 378–382.

. Ghazaly, N. M. . (2022). Data Catalogue Approaches, Implementation and Adoption: A Study of Purpose of Data Catalogue. International Journal on Future Revolution in Computer Science &Amp; Communication Engineering, 8(1), 01–04.