Revolutionizing Agriculture through IoT Enhanced Data Analytics: A Study from a Blockchain Technology Perspective
Authors: S. Sivabalan  , R. Renugadevi  , G. Kalaiarasi  , R. Rathipriya  , A. Loganathan  
Published: January 2025

The emergence of interconnected systems, blockchain approaches, and the
Internet of Things (IoT) is creating novel possibilities for information-driven choices in
agricultural production. The knowledge provided in this chapter points out the
innovative possibilities of integrated technologies with respect to small-to-large scale,
wholesale, vendor, end user, and sustainable farmland. The aim of this study is to
incorporate hyperledger formulation in a decentralized blockchain building with the
Internet of Things gadgets in automated agriculture. This involves placing actuators
and sensing devices on the ground to develop an infrastructure of coupled gadgets that
continuously acquire and convey data from the realm of agriculture. This section
outlines data collection methods practiced in agriculture using IoT devices as well as
blockchain. It emphasizes wired and wireless connectivity and describes the types of
sensors used to monitor soil conditions, weather patterns, crop health, and other
relevant parameters. An example is that farmers may receive weather- and climatepredicted data promptly. The heart of the research is to understand the study on data
analysis in the agricultural sector using blockchain technology. From descriptive
analysis for historical data review to predictive analysis for forecasting crop yields and
disease attacks, this section provides an overview of the techniques in practice. It
examines the increasing trend towards the adoption of edge computing in agriculture,
enabling real-time data analysis directly from the ground, which may reduce latency,
improve decision-making speed, and reduce the need for centralized cloud processing.
The concluding portion addresses pragmatic applications for unified systems in IoTdriven statistical analysis and agribusiness. Supply chain (SC) optimization,
surveillance of crops, smart watering systems, and agricultural precision farming are several examples. Identifying a handful of the complications that arise with this
scientific convergence, the study examines pitfalls that parties in the agricultural sector
have to navigate. It involves prerequisites for suitable physical labor, cooperation
hardships, and data safety worries. New technologies designed to address the foregoing
problems and efforts to fix those conflicts with farm-integrated IoT-driven data
visualization are looked at along with their demonstrated intelligent farming
approaches. Prospective paths in IoT-driven information mining and a system with
embedded components for agriculture-related access without agent marketing are laid
out in the investigation's summary. The work discusses the potential effects of artificial
intelligence (AI) and machine learning (ML) promotions, strengthened sensory
technological advances, and the possible incorporation of blockchain for safeguarding
data and the ability to track individuals for sustainable farming and planetary food
sustainability. The investigation of embedded equipment and IoT-driven analytical
methods in the agricultural industry is addressed in this scientific statement. It offers an
explanation of the manner in which agribusiness is adapting to herald in an additional
phase of ecological responsibility, preciseness, and operational effectiveness.