AI-Aided Sustainable IoT System: Theories, Techniques, and Applications

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Artificial Intelligence".

Deadline for manuscript submissions: 15 October 2024 | Viewed by 697

Special Issue Editors


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Guest Editor
1. Department of Electronic Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
2. CIX Technology (Shanghai) Co., Ltd., Shanghai 201203, China
Interests: artificial intelligence and machine learning for wireless, green Internet of Things system; modeling and algorithm design
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
School of Electronic Information and Communications, Huazhong University of Science and Technology, Wuhan 430074, China
Interests: heterogeneous and femtocell-overlaid cellular networks; wireless ad hoc networks; stochastic geometry; point process theory
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Department of Electronic Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
Interests: multiple access; coded cooperation; green heterogeneous networks

Special Issue Information

Dear Colleagues,

The global mobile data traffic market is projected to grow from 84 million terabytes per month in 2022 to 603.5 million by 2030. The sustainable Internet of Things (IoT) system has emerged as a proactive response to the mounting energy consumption concerns arising from the rapid proliferation of IoT devices and technologies. In propelling the development of the sustainable IoT system, Artificial Intelligence (AI)-based techniques play important roles. State-of-the-art AI-based technologies in signal processing, wireless communications, embedded systems, and smart computing could be helpful in adding intelligence to the sustainable IoT system. This Special Issue is dedicated to exploring the latest developments of AI-based technologies in the sustainable IoT system with a specific focus on showcasing innovative solutions that augment their capabilities and applications.

The topics of interest for this Special Issue include but are not limited to:

  • Intelligent information theory;
  • Intelligent signal processing;
  • Wireless artificial intelligence;
  • Green intelligent communication and computing;
  • Deep neural networks;
  • Intelligent image processing;
  • Statistical signal modeling;
  • Integrated circuits simulations;
  • Big data analysis;
  • Machine learning applications;
  • Artificial intelligence applications;
  • Internet of Things.

Dr. Yuchao Chang
Dr. Yi Zhong
Prof. Dr. Wen Chen
Guest Editors

Manuscript Submission Information

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Keywords

  • artificial intelligence
  • IoT
  • big data
  • signal processing

Published Papers (1 paper)

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Research

46 pages, 12068 KiB  
Article
Intelligent Regulation of Temperature and Humidity in Vegetable Greenhouses Based on Single Neuron PID Algorithm
by Song Huang, Huiyu Xiang, Chongjie Leng, Tongyang Dai and Guanghui He
Electronics 2024, 13(11), 2083; https://doi.org/10.3390/electronics13112083 - 27 May 2024
Viewed by 274
Abstract
In order to meet the demands of autonomy and control optimization in solar greenhouse control systems, this paper developed an intelligent temperature and humidity control system for greenhouses based on the Single Neuron Proportional Integral Derivative (SNPID) algorithm. The system is centered around [...] Read more.
In order to meet the demands of autonomy and control optimization in solar greenhouse control systems, this paper developed an intelligent temperature and humidity control system for greenhouses based on the Single Neuron Proportional Integral Derivative (SNPID) algorithm. The system is centered around the Huada HC32F460 Micro-Controller Unit (MCU) and the RT-Thread operating system, integrated with the SNPID control algorithm. Through comprehensive simulation, model construction, and comparative experiments, this system was thoroughly evaluated in comparison with traditional PID control systems (cPID) that rely on overseas software and hardwsbuare. Simulation results show that our new system significantly outperforms traditional PID (Proportional Integral Derivative) systems in terms of temperature control stability and accuracy. Experimental data further confirm that, while ensuring cost-effectiveness, the new system achieves a remarkable 50.2% improvement in temperature and humidity control precision compared to traditional systems. The temperature Root Mean Square Error (RMSE) in the experimental greenhouse is 0.734 compared to 1.594 in the comparison greenhouse, indicating better stable temperature control capability. The vents in the experimental greenhouse have a maximum opening of 67 cm and a minimum of 5 cm, showing a quick response property to high temperatures. In contrast, the control greenhouse has a maximum vent opening of 55 cm, remaining unchanged during the test period, which reflects its slower response to temperature fluctuations. These results demonstrate the significant advantages of the designed solar greenhouse temperature and humidity control system in terms of autonomy and control optimization, providing an efficient and economical solution for solar greenhouse environmental management. This system shows significant practical application perspective in promoting intelligent agriculture and sustainable agricultural production, highlighting its broad impact and potential significance. Full article
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