An IoT Based System for Smart Farm Pest and Disease Control in India

This project proposes the development of an IoT-based system for smart farms in India, focusing on pest and disease control for crops such as tomatoes, vegetables, cucumbers, maize, kales, and tea leaves. The system aims to utilize IoT technology with sensors to monitor and detect pest infestations and diseases at an early stage. The detected data is sent to farmers through a cloud-based system, providing information and mitigation measures in the local language via a mobile application. The project employs content analysis methodology, including questionnaires, surveys, interviews, and literature review to analyze existing research on IoT applications in agriculture. The goal is to improve food security by reducing crop losses, offering an alternative to the traditional use of chemicals for pest and disease management. The system will also track weather patterns to predict potential infestations and propose solutions, making it a comprehensive tool for farmers.

Annotated bibliography
Duncan, N. B. (1995). Capturing flexibility of information technology infrastructure: A study of
resource characteristics and their measure. Journal of management information
systems, 12(2), 37-57.
The research employed used of discussion, questionnaires and surveys. Authors used
constructions of information designs and discussed the results that gave exact measures of
designs. Arrangement of innovative designs to field-tested strategies is introduced as basic to
framework adaptability and adequacy. The study recommends that foundation adaptability may
be influenced by a sort of help from business, for example, the requirement for foundation and IT
initiative in getting ready for and dealing with certain assets. The creator infers that both business
furthermore, IT capacities may mirror the adaptability of the foundation segments.
R. Morris, Computerized Content Analysis in Management Research: A Demonstration of
Advantages & Limitations, Journal of Management, vol. 20, no. 4, pp. 903-931, 1994.
Available: 10.1177/014920639402000410
The author uses content analysis as the methodology and the concept being discussed
here is the “computerizing research”. The study described content analysis as the most used
method of research projects. It involves identifying of sources relevant to the subject, compiling
the list of that literature and scanning to verify the authenticity of their content. The research
focused on using computerized sources or media sources instead of using human skills. The
study found out that media content analysis has more resources than the use of traditional library
and undocumented conferences. The concludes that media is the largest source of information for
virtually every research.

P. van Oorschot and S. Smith, "The Internet of Things: Security Challenges", IEEE Security &
Privacy, vol. 17, no. 5, pp. 7-9, 2019. Available: 10.1109/msec.2019.2925918.
The study uses directed content analysis as the project research methodology. It covers
several literatures on internet security. First giving a proper definition of internet of things and
the things that make up internet of things using literatures on the said subject. The study found
out that there are security loopholes in the system such as; software validation, authority to
access data, privacy, system hacking and the vulnerability of system connected to many devices.
They recommend use of other technologies such as blockchain to secure Internet of Things
applications.
Patil, A. S., Tama, B. A., Park, Y., & Rhee, K. H. (2017). A framework for blockchain based
secure smart greenhouse farming. In Advances in Computer Science and Ubiquitous
Computing (pp. 1162-1167). Springer, Singapore.
The paper uses conceptual and content analysis methods of research. The authors used
interviews, surveys and literature available to come up with a conclusive paper on blockchain
technology on greenhouse farming. Green house farming that uses internet of things need a
system that can be used to secure the farms and the produce. The authors infer that blockchain
can be used to secure greenhouse farming because of its security features of proof of work,
system validation, protection of password, smart contract etc. they argued that, these features
will help improve the security of greenhouse farms.