A Comparative Analysis on Smart Farming Techniques using Internet of Things (IoT)

Author Name(s): Pramod Mathew Jacob, Prasanna M, Parveen Sultana H
Author Email: pramod3mj@gmail.com

Abstract

Agriculture is considered as one of the major sources in maintaining a nation’s GDP. Most of the developing countries and under developed countries are relying on cultivation to improve their economic wealth. In this modern technology era, technology can play a tremendous role in the agriculture sector. The advanced technology has the capability to automate various cultivation phases like watering, fertilizing, harvesting and much more. In order to make the cultivation phases smarter, we deploy smart sensors in the fields to sense the water level, photo sensors to ensure sufficient sunlight is available for plant’s growth, sensors to sense the nitrogen content and thereby to inform the farmer to initiate steps for proper fertilizing, etc. There are many works done in this area, and much more is progressing in the labs now. We analyzed the various standard IoT techniques used in Agriculture sector based on hardware and software, and thereby deriving the existing challenges for making farming much smarter and efficient.

Introduction

Internet of Things (IoT) is a term which was quite unfamiliar to ordinary people in older days. But in this era of smart technology and smarter systems, IoT became much popular. IoT is an emerging field which can play a vital role in almost all fields and disciplines including agriculture, health sector, home automation, aviation and transport, defense and military applications and much more. The Internet of things (stylized Internet of Things or IoT) is the internetworking of physical devices, vehicles (also referred to as “connected devices” and “smart devices”), buildings, and other items—embedded with electronics, software, sensors, actuators, and network connectivity that enable these objects to collect and exchange data. IoT can be used to make the objects or things smarter by remotely sensing or controlling it. Internet of Things comprises things that have unique identities and are connected to the internet [2]. IoT describes a system consist of various items in the physical world, and sensors within or attached to these items which are connected to the Internet via wireless and wired Internet connections. These sensors can use various types of local area connections such as RFID, NFC, Wi-Fi, Bluetooth, and Zig-bee. Sensors can also have wide area connectivity such as GSM, GPRS, 3G, and LTE.

Conclusion

Internet of Things (IoT) is playing an appreciable role in all fields of the globe like agriculture, aviation, transport, health care, etc. Our work reviews the growth and progress of IoT-based system used in the agriculture sector and in smart farming. It all started by using Zig-bee based Wireless Sensor Networks (WSN) later followed by centralized IoT boards and processors like Arduino, Raspberry PI, etc. They are using a wide set of sensors like temperature and humidity sensor, light sensor, soil moisture sensor, pH sensor, PIR motion sensor, etc. The main challenge for the researchers in this area is to design more accurate and useful sensors that will aid in monitoring plant growth. Power management to the sensors and central system is also a constraint. Designers should opt for low powered intelligent sensors and board to use the power efficiently. On the software side our analysis may help the software architect to choose the suitable pattern for their IoT use case. Our review analysis shows that IoT is still an exploring area for the researchers to make the farming much smarter by designing much smarter objects or things using secure and interoperable software architectures.

References

T. Qiu, J. Liu, W. Si, M. Han, H. Ning and M. Atiquzzaman, “A Data-Driven Robustness Algorithm for the Internet of Things in Smart Cities,” in IEEE Communications Magazine, vol:55, no:12, p. 18-23, DECEMBER 2017.
A. Bahga and V. MAdisetti, Internet of Things: A hands on approach, Universities Press, First edition, ISBN: 97888173719547.
Y. Erlich, “A vision for ubiquitous sequencing,” Genome Research, ISSN 1088-9051, 2015,  p. 1411–1416.
L. Dan, C. Xin, H. Chongwei and J. Liangliang, “Intelligent Agriculture Greenhouse Environment Monitoring System Based on IOT Technology,” International Conference on Intelligent Transportation, Big Data and Smart City, Halong Bay, 2015.
“Zigbee,” Digi, Available at: https://www.digi.com/resources/standards-and-technologies/rfmodems/zigbee-wireless-standard. [Accessed 2017 March 20].
V. V. h. Ram, H. Vishal, S. Dhanalakshmi and P. M. Vidya, “Regulation of water in agriculture field using Internet Of Things,” IEEE Technological Innovation in ICT for Agriculture and Rural Development (TIAR), Chennai, 2015.
J. Shenoy and Y. Pingle, “IOT in agriculture,” 3rd International Conference on Computing for Sustainable Global Development (INDIACom), New Delhi, 2016.

“Polyhouse farming advantages and benefits”, Available at: http://www.agrifarming.in/polyhouse-farming-profits/. [Accessed 3 March 2017].
“Soil pH,” Wikipedia, Available at: https://en.wikipedia.org/wiki/Soil_pH. [Accessed 4 March 2017].
A. Abdullah, S. A. Enazi and I. Damaj, “AgriSys: A smart and ubiquitous controlled-environment agriculture system,” 3rd MEC International Conference on Big Data and Smart City (ICBDSC), Muscat, 2016.
“Multiple Input Multiple Output (MIMO),” Radio Electronics.com, [Online]. Available: http://www.radio-electronics.com/info/antennas/mimo/multiple-input-multiple-output-technology-tutorial.php. [Accessed 26 March 2017].
N. Gondchawar and R. S. Kawitkar, “Smart Agriculture Using IoT and WSN based Modern technologies,” International Journal of Innovative Research in Computer and Communication Engineering, vol:4, no:6, 2016.
“Raspberry PI”,  Available at: https://www.raspberrypi.org/. [Accessed 22 March 2017].
S. K. Nagothu, “Weather based smart watering system using soil sensor and GSM,” 2016 World Conference on Futuristic Trends in Research and Innovation for Social Welfare (Startup Conclave), Coimbatore, 2016.
N. Agrawal and S. Singhal, “Smart drip irrigation system using raspberry pi and arduino,”   International Conference on Computing, Communication & Automation, Noida, 2015.
“Arduino,” Arduino, Available at: https://www.arduino.cc/. [Accessed 24 March 2017].
N. Putjaika, S. Phusae, A. Chen-Im, P. Phunchongharn and K. Akkarajitsakul, “A control system in an intelligent farming by using arduino technology,” Fifth ICT International Student Project Conference (ICT-ISPC), Nakhon Pathom, 2016.
S. Khashirunnisa, B. K. Chand and B. L. Kumari, “Performance analysis of Kalman filter, fuzzy Kalman filter and wind driven optimized Kalman filter for tracking applications,” 2nd International Conference on Communication Control and Intelligent Systems, Mathura India, 2016 .
A. Kapoor, S. I. Bhat, S. Shidnal and A. Mehra, “Implementation of IoT (Internet of Things) and Image processing in smart agriculture,” International Conference on Computation System and Information Technology for Sustainable Solutions (CSITSS), Bangalore, 2016.

C. A. et. al, “Wireless sensing and control for precision Green house management,” Sixth International Conference on Sensing Technology (ICST), Kolkata, 2012.
P. M. Jacob, Muhammed Ilyas H, J. Jose and J. Jose, “An Analytical approach on DFD to UML model transformation techniques,” 2016 International Conference on Information Science (ICIS), Kochi, 2016, pp. 12-17.
Mary Shaw, David Garlan, ‘Software Architecture: Perspectives on an Emerging Discipline’, Prentice Hall, 1996.
Y. Ducq and D. Chen, ‘How to measure interoperability: Concept and approach,’ 2008 IEEE International Technology Management Conference (ICE), Lisbon, 2008, pp. 1-8.
P. M. Jacob and M. Prasanna, “A Comparative analysis on Black box testing strategies,” 2016 International Conference on Information Science (ICIS), Kochi, 2016, pp. 1-6.

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