Agricultural development is one of the powerful tools to boost the economy of any developing country. The recent advancement of IoT-based smart agriculture systems helps to achieve more productivity with relatively less overhead. The Department of Computer Science and Engineering is glad to announce that their faculty; Dr Sobin CC, Associate Professor; Dr Sonam Maurya, Assistant Professor; and Dr Amit Kumar Singh, Assistant Professor; have published a patent titled “Smart Agriculture System using Delay Tolerant Internet of Things” (Application No. 20224102799), a framework for smart agricultural applications using Delay Tolerant Internet of Things (DT-IoT) which can handle the issues related to disruptions in network connectivity.

The inherent limitations of IoT-based smart agriculture systems majorly in terms of resource constraints, frequent network disconnections and vulnerability to many attacks may affect their advantages over the traditional systems. The application using DT-IoT, with access to greater network connectivity can deliver relevant data in real-time. Furthermore, the stored data can be processed and analysed to help farmers in making critical decisions related to their farm filed. Hence, their innovation focuses on designing and developing a prototype for a smart agricultural application using the Internet of Things (IoT).

One of the simplest outcomes of providing smart agricultural solutions for remote villages in India will be greater support to the farmers to improve their productivity and better decision-making in cultivation. But advanced technologies need Internet connectivity in the field to function, which is still a dream in many of the remote villages in India. The lack of proper communication facilities faces off the application of IoT networks. This fact has motivated them to propose a smart agricultural system to work on agricultural application issues using delay-tolerant characteristics. The use of delay-tolerant features in traditional IoT provides a solution for smart agriculture which can handle issues related to disruptions in connection to improve communications.

Another important aspect is that many of the applications, including IoT/Sensor networks, are either simulation-based or experimental. A very few of the applications are developed and implemented in the real-time field for the benefit of farmers in remote villages. In most of the remote villages in India, most of the farmers are poor, many of them are even without primary school education and they rely mostly on traditional agricultural practices which they received from their previous generations. Therefore, their study proposed to test and implement the smart agricultural system with real-time automated solutions related to irrigation, controlled fertilisation, cultivation, production quality, quantity, crop health etc. using IoT with delay-tolerant support. They are also in the process of collaborating with academia and industry to execute this project.

Social Implications

• Proposed smart agriculture system will assist in real-time monitoring of farm field conditions, like irrigation, soil quality, and nutrient deficiency.
• It provides support to farmers to improve their productivity and decision-making in crop cultivation.
• The proposed system will provide optimization in terms of seed selection, resource utilisation, planning cultivation, marketing, harvest quality, etc., using Machine Learning techniques.
• Agricultural field data analysis (for data collected by the large group of sensors) and its visualisation.
• Weather prediction (for better planning).
• Price prediction (for better marketing strategies).

Fig 1: Main components of the proposed Smart Agriculture System

Fig 2: Illustration of 3-level architecture implementation in the Smart Agriculture System

Rohan Reddy Sambidi received admission offers with scholarships upto $16,500

Rohan Reddy Sambidi from Btech CSE at SRM University-AP is delighted to have received admission offers from numerous universities abroad. He secured admission to MS in Computer Science at Purdue University, Fort Wayne; Texas A&M University, College Station (Distance); Arizona State University, Tempe; Illinois Institute of Technology, Chicago; University of South Florida, Tampa; and the University of Houston. Along with this, he received an offer from the University of Maryland, College Park for the Master of Professional Studies in Machine Learning programme. Admission offers came with a scholarship of $10,000 from ASU and $16,500 from IIT Chicago.

The suitable choice

Rohan has decided to join the MS in Computer Science programme at Arizona State University. He plans to prepare a thesis and focus his research on the field of machine learning. He wants to explore and address the challenges of designing efficient deep learning algorithms for space exploration through telescopic imagery. He is also interested in doing a few courses on theoretical computer science.

Finding the best

For selecting universities, Rohan started by acquiring a list of reputed universities from the QS Rankings website. Then he shortlisted universities by focusing on the course curriculum, faculty, and resources for student research. He has completed his bachelor’s degree at SRM university-AP with a major in Computer Science and Engineering and a minor in Physics.

Support from SRM AP

The mentorship of accomplished faculty has helped Rohan build strong foundational knowledge in his discipline. Through the course projects, UROP, and the Capstone Project, he has developed research skills and built a compelling profile essential for admission to leading universities in the USA. He expressed his gratitude to his professors and mentors, Prof Dr Ragunathan T, Dr Jatindra Kumar Dash, and Dr Murali Krishna Enduri, for their relentless guidance. He is immensely grateful for the opportunities that he received from SRM university-AP.