Design and Optimization of an Internet of Things-Based Cloud Platform for Autonomous Agricultural Machinery Using Narrowband Internet of Things and 5G Dual-Channel Communication

This paper proposes a design and optimization scheme for an Internet of Things (IoT)-based cloud platform aimed at enhancing the communication efficiency and operational performance of autonomous agricultural machinery. The platform integrates the dual communication capabilities of Narrowband Intern...

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Vydáno v:Electronics (Basel) Ročník 14; číslo 8; s. 1672
Hlavní autoři: Zhao, Baidong, Zheng, Dingkun, Yang, Chenghan, Wang, Shuang, Mansurova, Madina, Jomartova, Sholpan, Kunicina, Nadezhda, Zabasta, Anatolijs, Beliaev, Vladimir, Caiko, Jelena, Grants, Roberts
Médium: Journal Article
Jazyk:angličtina
Vydáno: Basel MDPI AG 20.04.2025
Témata:
Agricultural equipment
Agricultural equipment and supplies industry
Agriculture
Algorithms
Clouds
Collaboration
Data transmission
Decision making
Design optimization
Efficiency
Energy consumption
Internet of Things
Narrowband
Network latency
Path tracking
Real time
Resource scheduling
Resource utilization
Sensors
Smoothness
Task scheduling
China
ISSN:2079-9292, 2079-9292
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Abstract This paper proposes a design and optimization scheme for an Internet of Things (IoT)-based cloud platform aimed at enhancing the communication efficiency and operational performance of autonomous agricultural machinery. The platform integrates the dual communication capabilities of Narrowband Internet of Things (NB-IoT) and 5G, where NB-IoT is utilized for low-power, reliable data transmission from environmental sensors, such as soil information and weather monitoring, while 5G supports high-bandwidth, low-latency tasks like task scheduling and path tracking to effectively address the diverse communication requirements of modern complex agricultural scenarios. The cloud platform improves operational efficiency and resource utilization through real-time task scheduling, dynamic optimization, and seamless coordination between devices. To accommodate the diverse operational demands of agricultural environments, the system incorporates a real-time data feedback mechanism leveraging sensor data for path tracking and adjustment, enhancing adaptability and stability. Furthermore, a multi-machine collaborative scheduling strategy combining Dijkstra’s algorithm and an improved Harris hawk optimization (IHHO) algorithm, along with a multi-objective optimized path tracking method, is introduced to further improve scheduling efficiency and resource utilization while improving path tracking accuracy and smoothness and reducing external interferences, including environmental fluctuations and sensor inaccuracies. Experimental results demonstrate that the IoT-based cloud platform excels in data transmission reliability, path tracking accuracy, and resource optimization, validating its feasibility in smart agriculture and providing an efficient and scalable solution for large-scale agricultural operations.
AbstractList This paper proposes a design and optimization scheme for an Internet of Things (IoT)-based cloud platform aimed at enhancing the communication efficiency and operational performance of autonomous agricultural machinery. The platform integrates the dual communication capabilities of Narrowband Internet of Things (NB-IoT) and 5G, where NB-IoT is utilized for low-power, reliable data transmission from environmental sensors, such as soil information and weather monitoring, while 5G supports high-bandwidth, low-latency tasks like task scheduling and path tracking to effectively address the diverse communication requirements of modern complex agricultural scenarios. The cloud platform improves operational efficiency and resource utilization through real-time task scheduling, dynamic optimization, and seamless coordination between devices. To accommodate the diverse operational demands of agricultural environments, the system incorporates a real-time data feedback mechanism leveraging sensor data for path tracking and adjustment, enhancing adaptability and stability. Furthermore, a multi-machine collaborative scheduling strategy combining Dijkstra’s algorithm and an improved Harris hawk optimization (IHHO) algorithm, along with a multi-objective optimized path tracking method, is introduced to further improve scheduling efficiency and resource utilization while improving path tracking accuracy and smoothness and reducing external interferences, including environmental fluctuations and sensor inaccuracies. Experimental results demonstrate that the IoT-based cloud platform excels in data transmission reliability, path tracking accuracy, and resource optimization, validating its feasibility in smart agriculture and providing an efficient and scalable solution for large-scale agricultural operations.
Audience Academic
Author Zhao, Baidong
Caiko, Jelena
Zheng, Dingkun
Yang, Chenghan
Jomartova, Sholpan
Wang, Shuang
Zabasta, Anatolijs
Grants, Roberts
Kunicina, Nadezhda
Beliaev, Vladimir
Mansurova, Madina
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CitedBy_id crossref_primary_10_3390_agriculture15111136
crossref_primary_10_1016_j_compag_2025_110952
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Snippet This paper proposes a design and optimization scheme for an Internet of Things (IoT)-based cloud platform aimed at enhancing the communication efficiency and...
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SubjectTerms Agricultural equipment
Agricultural equipment and supplies industry
Agriculture
Algorithms
Clouds
Collaboration
Data transmission
Decision making
Design optimization
Efficiency
Energy consumption
Internet of Things
Narrowband
Network latency
Path tracking
Real time
Resource scheduling
Resource utilization
Sensors
Smoothness
Task scheduling
Title Design and Optimization of an Internet of Things-Based Cloud Platform for Autonomous Agricultural Machinery Using Narrowband Internet of Things and 5G Dual-Channel Communication
URI https://www.proquest.com/docview/3194581591
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