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Topic Title:

Intelligent Automation for Smart Agriculture: From Sensor Networks to Decision Support Systems

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Submission Deadline:

5 December 2023


Topic Editors:

  • Dr. Muhammad Shafiq (IEEE Senior Member), Distinguished Associate Professor at Cyberspace Institute of Advanced Technology, Guangzhou University, Guangzhou, China

  • Prof. Ihsan Ali (IEEE Senior Member), University of Nebraska, Omaha, USA

  • Prof. Gautam Srivastava (IEEE Senior Member), Brandon University, Brandon, Canada

  • Prof. Tian Zhihong (IEEE Senior Member), Guangzhou University, Guangzhou, China

  • Prof. Jingheng Zhang, Hangzhou Dianzi University, Hangzhou, China

  • Assistant Prof. Mukhtar Ahmed, PMAS Arid Agriculture University Rawalpindi, Pakistan



The agricultural industry must produce more food while ensuring environmental sustainability and efficient resource usage to meet the global population's demand, set to hit 9.7 billion by 2050. Advanced technologies and automation are critical solutions for this challenge. Sensor networks, machine learning, and decision support systems integrated into intelligent automation are promising approaches that can help address this challenge. These technologies have the potential to transform the way agriculture is practiced and lead to improved crop yields, reduced environmental footprint, and optimized food production.

Cross-disciplinary collaboration between researchers, farmers, and technology experts is necessary to develop and implement intelligent automation solutions for smart agriculture. The latest advancements in sensor technologies and machine learning techniques can efficiently analyze and interpret the collected data.

The special issue aims to investigate the latest developments in intelligent automation for smart agriculture, focusing on sensor networks and decision support systems.

The issue will cover topics such as designing and implementing sensor networks for monitoring crop growth and environmental conditions, machine learning algorithms for analyzing sensor data, and case studies of intelligent automation systems in real-world agricultural settings. This special issue allows researchers and practitioners to share their findings and perspectives for enhanced agricultural productivity, sustainability, and environmental performance.


Authors are invited to submit original research articles, review articles, or case studies. The papers should not have been previously published or are currently under review for any other journal or conference. All submissions will be peer-reviewed to ensure high-quality contributions.



1. Intelligent sensing technology of crop information

2. Smart sensor networks for precision agriculture

3. Models for monitoring and predicting crop growth and stress state

4. Autonomous robots for farm operations

5. Decision support systems for crop management

6. Machine learning techniques for yield prediction

7. Optimization algorithms for resource management

8. Real-time monitoring and control of agriculture systems

9. Data Analytics for agricultural decision-making


Participating Journals:

Intelligent Automation & Soft Computing

Phyton-International Journal of Experimental Botany

Topic Title:

AI in Energy System Applications

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Submission Deadline:

30 November 2023


Topic Editors:

  • Dr. Hamed Hashemi-Dezaki, University of Kashan, Iran 

  • Dr. Ali Karimi, University of Kashan, Iran 

  • Dr. Bo Yang, Kunming University of Science and Technology, China

  • Dr. Dongran Song, Central South University, China 

  • Dr. Ali Khosravi, University of Southern Denmark, Denmark

  • Dr. Mohamed Talaat, Zagazig University, Egypt



Artificial intelligence (AI) is a key enabler in transforming the energy sector, particularly with the emergence of smart grids that integrate renewable energy sources, distributed generations (DGs), energy storage systems, and other concepts, like demand response. AI can help optimize the operation and management of smart grids and energy systems by leveraging data from sensors, meters, devices, and users. AI can also support the innovation and design of new energy materials and devices, automate complex energy processes and systems, and provide insights into the human and social aspects of energy use and policy. However, applying AI to energy also poses some technical and ethical challenges, such as ensuring data quality and availability, validating and verifying AI models and solutions, balancing trade-offs between performance and explainability, and ensuring fairness, accountability, and transparency of AI decisions and impacts.


This special issue aims to showcase the latest research progress and innovations in the cross-disciplinary area of AI and energy, focusing on the applications of AI to smart grids, energy systems, power systems, and related topics, such as Internet-of-Things (IoT), machine learning, deep learning, smart metering, smart buildings, smart cities, microgrids, distributed energy resources (DERs), electric vehicles (EVs), cyberphysical systems (CPSs), and cyber-security. The special issue welcomes original research articles, short communications, perspective articles, and review articles that demonstrate the potential and impact of AI in various domains of energy systems and smart grids, such as planning, operation, control, optimization, protection, reliability, resilience, stability, forecasting, pricing, market design, customer engagement, and demand response. The special issue also encourages submissions that address the challenges and opportunities of applying AI to energy systems in the context of sustainable development goals.



1. Emerging trends and future directions for Artificial Intelligence (AI) in energy systems

2. Integration of artificial intelligence (AI) to energy systems

3. Internet of Things (IoT)

4. Data analytics

5. Machine learning (ML)

6. Deep learning (DL)

7. Smart grids

8. Microgrids

9. Internet-of-Things (IoT)

10. Renewable energy

11. Energy efficiency

12. Energy forecasting

13. Energy optimization

14. Energy management

15. Energy policy

16. Decision-making under uncertainty

17. Electric vehicles

18. Artificial neural networks (ANNS) and energy systems

19. Power market


Participating Journals:

Intelligent Automation & Soft Computing

Energy Engineering

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