Agricultural Informatics. Группа авторов
Читать онлайн книгу.
Result
2.7.4 Processor Showdown
BeagleBone Black is nearly 2 times as fast as Raspberry Pi.
Winner:BeagleBone Black.
2.7.5 Right Choice for Projects
| BeagleBone Black | Raspberry Pi |
| 1. Projects that need to interface plenty of External Sensors. | 1. Multimedia based Projects. |
| 2. High Speed Processing. | 2. Community Driven. |
| 3. Commercialization Projects. | 3. Graphical Learning Platform |
| 4. Embedded System Learning | 4. Internet Connected Projects. |
2.8 Conclusions
The proposed integrated Agro-IoT system tends to integrate the earlier problems faced in the previous smart farming as well as tried to find out the solution for the same. Thus all the traditional monitoring problems faced by one farmer get solved by getting together in a one integrated agro-IoT system. The researchers have succeeded in reaching their objective and they made the whole system efficient for the upcoming modern farming era.
2.9 Future Work
The prototype model of the proposed system can be built up in real farming area to replace the traditional monitoring system of farmers in the field. With the advancement of upcoming technology, the agro-IoT system can be more advanced in future.
References
1. Liqiang, Z., Shouyi, Y., Leibo, L., Zhen, Z., Shaojun, W., A crop monitoring system based on wireless sensor network. Procedia Environ. Sci., 11, 558–65, Jan, 2011.
2. Zhu, Y., Song, J., Dong, F., Applications of wireless sensor network in the agriculture environment monitoring. Procedia Eng., 16, 608–14, Jan, 2011.
3. Jaishetty, S.A. and Patil, R., IoT sensor network based approach for agricultural field monitoring and control. IJRET: Int. J. Res. Eng. Technol., 5, 06, Jun, 2016.
4. Keerthi.v and Kodandaramaiah, G.N., Cloud IoT Based greenhouse Monitoring System. Int. J. Eng. Res. Appl., 5, 10, (Part—3), 35–41, 2015.
5. Srisruthi, S., Swarna, N., Susmitha Ros, G.M., Elizabeth, E., Sustainable Agriculture using Eco-friendly and Energy Efficient Sensor Technology. IEEE International Conference On Recent Trends In Electronics Information Communication Technology, May 2016.
6. Mathurkar, S.S., Lanjewar, R.B., Patel, N.R., Somkuwar, R.S., Smart Sensors Based Monitoring System for Agriculture using Field Programmable Gate Array. International Conference on Circuit, Power and Computing Technologies [ICCPCT], 2014.
7. Channe, H., Kothari, S., Kadam, D., Multidisciplinary model for smart agriculture using internet-of-things (IoT), sensors, cloud-computing, mobile-computing & big-data analysis. Int. J. Comput. Technol. Appl., 6, 3, 374–382, Apr. 2015.
8. Satyanarayana, G.V. and Mazaruddin, S.D., Wireless Sensor Based Remote Monitoring System for Agriculture using ZigBee and GPS. Conference on Advances in Communication and Control Systems, 2013.
9. Sakthipriya, N., An Effective Method for Crop Monitoring Using Wireless Sensor Network. Middle East J. Sci. Res., 20, 9, 1127–1132, 2014.
10. Kumar, S. and Somani, V., Social Media Security Risks, Cyber Threats And Risks Prevention And Mitigation Techniques. Int. J. Adv. Res. Comput. Sci. Manag., 4, 4, 125–9, 2018.
11. Baggio, A., Wireless Sensor Networks in Precision Agriculture, in: ACM Workshop Real-World Wireless Sensor Networks, 2005.
12. Kavitha, T., Preethi, D.L., Saranya, S., Evert, P.J.A., Realizing IoT based real time monitoring and controlling system. i-manager’s J. Comput. Sci., 4, 4, 20–24, 2017.
13. George, T., Bagazonzya, H., Ballantyne, P., Belden, C., Birner, R., Castello, R.D., Castren, T., Choudhary, V., Dixie, G., Donovan, K., Edge, P., ICT in agriculture: Connecting smallholders to knowledge, networks, and institutions. The World Bank, Nov 1, 2011.
14. Entekhabi, D. et al., The Soil Moisture Active Passive (SMAP) mission. Proc. IEEE, 98, 5, 704–716, 2010.
15. Nandurkar, S.R., Thool, V.R., Thool, R.C., Design and Development of Precision Agriculture System Using Wireless Sensor Network. IEEE International Conference on Automation, Control, Energy and Systems (ACES), 2014.
16. Liqiang, Z., Shouyi, Y., Leibo, L., Zhen, Z., Shaojun, W., A crop monitoring system based on wireless sensor network. Procedia Environ. Sci., 11, 558–65, Jan, 2011.
17. Priya, C.T., Praveen, K., Srividya, A., Monitoring of pest insect traps using image sensors & dspic. Int. J. Eng. Trends Tech., 4, 9, 4088–93, Sep, 2013.
18. Shalini, D.V., Automatic Pesticide Sprayer for Agriculture Purpose. IJSART, 2, 7, July, 2016.
19. Baranwal, T. and Pateriya, P.K., Development of IoT based smart security and monitoring devices for agriculture. In: 2016 6th International Conference-Cloud System and Big Data Engineering (Confluence), IEEE, pp. 597–602, Jan, 2016.
20. Kapoor, A., Bhat, S., II, Shidnal, S., Mehra, A., Implementation of IoT and Image Processing in Smart Agriculture. 2016 International Conference on Computational Systems and Information Systems for Sustainable Solutions.
21. Rajan, P., Radhakrishnan, B., Suresh, L.P., Detection and classification of pests from crop images using Support Vector Machine, in: Emerging Technological Trends (ICETT), International Conference on, 2016, October, IEEE, pp. 1–6.
22. Sladojevic, S., Arsenovic, M., Anderla, A., Culibrk, D., Stefanovic, D., Deep neural networks based recognition of plant diseases by leaf image classification. Comput. Intell. Neurosci., 2016, 1–11, May, 2016.
23. Rajesh, D., Application of spatial data mining for agriculture. Int. J. Comput. Appl., 15, 2, 7–9, Feb, 2011.
24. Borgia, E., The Internet of things: Key features, applications and open issues. Comput. Commun., 54, 1–31, Dec. 2014.
25. Manju, M., Karthik, V., Hariharan, S., Sreekar, B., Real time monitoring of the environmental parameters of an aquaponic system based on Internet of