Azure-based multi-sensor IoT network for smart rice-nursery field

Muhammad Juman Jhatial; Riaz Ahmed Shaikh; Rafaqat HussainArain; Khalid Hussain Bhutto; Sawan Talpur

Author(s)

Muhammad Juman Jhatial Computer Science, Shah Abdul Latif University,Khairpur Mirs, Sindh,Pakistan

Riaz Ahmed Shaikh Computer Science, Shah Abdul Latif University,Khairpur Mirs, Sindh,Pakistan

Rafaqat HussainArain Computer Science, Shah Abdul Latif University,Khairpur Mirs, Sindh,Pakistan

Khalid Hussain Bhutto Computer Science, Shah Abdul Latif University,Khairpur Mirs, Sindh,Pakistan

Sawan Talpur Computer Science, Shah Abdul Latif University,Khairpur Mirs, Sindh,Pakistan

Abstract

Rice farmers rely on nurseries for various reasons, as they play a pivotal role in cultivating high-quality rice crops. These nurseries provide essential seedlings for subsequent transplantation to the paddy fields. The success of rice cultivation hinges on maintaining a robust and thriving nursery, resulting in improved yields and superior grain quality. To enhance nursery management, a novel method proposes real-time monitoring of environmental conditions. A trial study evaluated the system's performance, demonstrating a significant increase in precision and efficiency, leading to higher crop yields and reduced production costs. This innovative approach has the potential to revolutionize rice nursery practices, promoting sustainability and effectiveness. The study introduces an Internet of Things (IoT)-based real-time monitoring system implemented in a rural area of Sindh, Pakistan. Utilizing a network of sensors, the system gathers vital environmental data that impacts rice nursery growth. The recorded information is then analyzed on the Azure cloud platform, and data visualization is achieved through Power BI. Additionally, an email notification component alerts farmers and agricultural experts based on the sensor data, facilitating timely actions and informed decision-making.

Publication Details

Page(s) 187-195

DOI DOI not available

Published Journal: VFAST Transactions on Software Engineering, Volume: 11, Issue: 2, Year: 2023

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Keywords

Sensors, raspberry pi, Power BI, IoT Hub, Azure cloud