Need for real-time monitoring in custom hiring centers (CHCs)

N. Sai Rama Krishna Harish, Sanwal Singh Meena
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Abstract

In India where mechanization is essential for national food security due to the country’s increasing population and food need agriculture is the main occupation. Considering that farm electricity availability is 3.045 kW/ha and that more than 85% of farmers are small (1–2 ha) or marginal (< 1 ha), they have little money to spend on expensive machinery. upto 2024–2025, 26,662 Custom Hiring Center (CHCs) will have been established to bridge this gap as well as offer a crucial tool to improve access to farm mechanization. This review examines the role challenges and opportunities of CHCs, focusing on integrating digital technologies. It proposes an IoT-, AI-, and ML-based real-time monitoring framework using secondary data sources. CHCs allow farmers to rent machinery when required, offering a more affordable option than individual ownership. However peak-season shortages lack of skilled operators, and inefficient scheduling limit their effectiveness. A framework integrating sensor-based real-time monitoring and digital platforms is proposed to enhance machinery utilization predictive maintenance operator efficiency and financial transparency evidence shows IoT- and AI-enabled systems can reduce downtime improve accessibility and lower operational costs strengthening CHC sustainability. In conclusion, digitally monitored CHCs supported by schemes like NMAM, NICRA, SMAM, NFSM, RKVY, and MIDH offer a cost-effective and sustainable pathway for farm mechanization.
定制招聘中心(CHCs)对实时监控的需求
在印度,由于人口和粮食需求的增加,机械化对国家粮食安全至关重要,农业是主要职业。考虑到农场电力供应为3.045千瓦/公顷,85%以上的农民规模小(1 - 2公顷)或边际(< 1公顷),他们几乎没有钱花在昂贵的机械上。到2024-2025年,将建立26,662个客户招聘中心(chc),以弥合这一差距,并为改善农业机械化提供重要工具。这篇综述探讨了CHCs的角色挑战和机遇,重点是集成数字技术。它提出了一个使用辅助数据源的基于物联网、人工智能和机器学习的实时监控框架。chc允许农民在需要时租用机器,提供了比个人拥有更实惠的选择。然而,旺季短缺,缺乏熟练的操作员,以及低效的调度限制了它们的有效性。提出了一个集成基于传感器的实时监控和数字平台的框架,以提高机械利用率、预测性维护操作员的效率和财务透明度。证据表明,支持物联网和人工智能的系统可以减少停机时间、提高可访问性并降低运营成本,从而增强CHC的可持续性。总之,由NMAM、NICRA、SMAM、NFSM、RKVY和MIDH等方案支持的数字监测chc为农业机械化提供了一条经济有效且可持续的途径。
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来源期刊
Discover Internet of Things
Discover Internet of Things Internet of Things (IoT)-
CiteScore
7.50
自引率
0.00%
发文量
6
审稿时长
28 days
期刊介绍: Discover Internet of Things is part of the Discover journal series committed to providing a streamlined submission process, rapid review and publication, and a high level of author service at every stage. It is an open access, community-focussed journal publishing research from across all fields relevant to the Internet of Things (IoT), providing cutting-edge and state-of-art research findings to researchers, academicians, students, and engineers. Discover Internet of Things is a broad, open access journal publishing research from across all fields relevant to IoT. Discover Internet of Things covers concepts at the component, hardware, and system level as well as programming, operating systems, software, applications and other technology-oriented research topics. The journal is uniquely interdisciplinary because its scope spans several research communities, ranging from computer systems to communication, optimisation, big data analytics, and application. It is also intended that articles published in Discover Internet of Things may help to support and accelerate Sustainable Development Goal 9: ‘Build resilient infrastructure, promote inclusive and sustainable industrialization and foster innovation’. Discover Internet of Things welcomes all observational, experimental, theoretical, analytical, mathematical modelling, data-driven, and applied approaches that advance the study of all aspects of IoT research.
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