𝙎𝙋𝙀𝘾𝙄𝘼𝙇 𝙄𝙎𝙎𝙐𝙀 𝙤𝙣 𝘼𝙄 𝙗𝙖𝙨𝙚𝙙 𝙏𝙚𝙘𝙝𝙣𝙞𝙦𝙪𝙚𝙨 𝙞𝙣 𝙒𝙞𝙧𝙚𝙡𝙚𝙨𝙨 𝙎𝙚𝙣𝙨𝙤𝙧 𝙉𝙚𝙩𝙬𝙤𝙧𝙠𝙨

This special issue in 𝗢𝗽𝗲𝗻 𝗖𝗼𝗺𝗽𝘂𝘁𝗲𝗿 𝗦𝗰𝗶𝗲𝗻𝗰𝗲 (𝗜𝗙 𝟮𝟬𝟮𝟮: 𝟭.𝟱) focuses on AI-based Techniques in Wireless Sensor Networks

AI-based techniques are becoming increasingly important in wireless sensor networks (WSNs) as they enable faster, more efficient, and more reliable decision-making. AI-based techniques can be used to improve the performance of a WSN, particularly when WSNs are deployed in an uncertain environment, such as in an industrial setting. AI-based techniques can enable a WSN to better adapt to its environment by making decisions about how to route data when to send data, and what data to send. AI-based techniques can also be used to detect anomalies and optimize the network by making decisions about how to allocate resources. AI-based techniques can also be used to identify and respond to security threats, detect and mitigate interference, and improve the accuracy of data collected. Finally, AI-based techniques can be used to reduce power consumption in a WSN by making decisions about when to turn off or on nodes and how to optimally schedule communication.

The ability of WSNs to collect and process data in real-time has made them particularly attractive for many applications. However, the data collected by WSNs is often noisy, inaccurate, and redundant, making it a challenge to extract meaningful information from the data. To address this challenge, AI-based techniques need to be employed in WSNs to enable data-driven approaches to manage and control the networks. AI based techniques can be used to analyze data in real-time and identify patterns, detect anomalies, and make decisions that can improve the performance, scalability, and security of WSNs.
Potential topics include:
• AI-based distributed sensing and communication techniques for Wireless Sensor Networks
• Learning and optimization algorithms for efficient data collection and transmission
• AI-based distributed algorithms for localization, tracking and routing
• AI-assisted secure communication in Wireless Sensor Networks
• AI-based energy harvesting and management in Wireless Sensor Networks
• Applications of AI in Wireless Sensor Networks
• AI-based cognitive radio networks
• AI-based spectrum sensing and spectrum sharing in Cognitive Radio Networks
• AI-based resource allocation and scheduling in Wireless Sensor Networks
• AI-based fault detection, diagnosis and recovery in Wireless Sensor Networks

Authors are requested to submit their full revised papers complying the general scope of the journal. The submitted papers will undergo the standard peer-review process before they can be accepted. Notification of acceptance will be communicated as we progress with the review process.

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𝑮𝑼𝑬𝑺𝑻 𝑬𝑫𝑰𝑻𝑶𝑹𝑺
Arvind Dhaka (Lead Guest Editor), Manipal University Jaipur, India
Siddhartha Chauhan, NIT Hamirpur, India,
Edmar Candeia Gurjao, Federal University of Campina Grande, Brazil
Amita Nandal, Manipal University Jaipur, India

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𝑫𝑬𝑨𝑫𝑳𝑰𝑵𝑬

The deadline for submissions is 𝗡𝗢𝗩𝗘𝗠𝗕𝗘𝗥 𝟯𝟬, 𝟮𝟬𝟮𝟯, but individual papers will be reviewed and published online on an ongoing basis.

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𝑯𝑶𝑾 𝑻𝑶 𝑺𝑼𝑩𝑴𝑰𝑻

All submissions to the Special Issue must be made electronically via the online submission system Editorial Manager:

𝗵𝘁𝘁𝗽𝘀://𝘄𝘄𝘄.𝗲𝗱𝗶𝘁𝗼𝗿𝗶𝗮𝗹𝗺𝗮𝗻𝗮𝗴𝗲𝗿.𝗰𝗼𝗺/𝗼𝗽𝗲𝗻𝗰𝘀/𝗱𝗲𝗳𝗮𝘂𝗹𝘁𝟮.𝗮𝘀𝗽𝘅

Please choose the article type “𝗦𝗜: 𝗔𝗜 𝗯𝗮𝘀𝗲𝗱 𝗧𝗲𝗰𝗵𝗻𝗶𝗾𝘂𝗲𝘀 𝗶𝗻 𝗪𝗶𝗿𝗲𝗹𝗲𝘀𝘀 𝗦𝗲𝗻𝘀𝗼𝗿 𝗡𝗲𝘁𝘄𝗼𝗿𝗸𝘀”.

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𝑪𝑶𝑵𝑻𝑨𝑪𝑻

𝗼𝗽𝗲𝗻𝗰𝗼𝗺𝗽𝘂𝘁𝗲𝗿𝘀𝗰𝗶𝗲𝗻𝗰𝗲@𝗱𝗲𝗴𝗿𝘂𝘆𝘁𝗲𝗿.𝗰𝗼𝗺

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𝗙𝗼𝗿 𝗺𝗼𝗿𝗲 𝗶𝗻𝗳𝗼𝗿𝗺𝗮𝘁𝗶𝗼𝗻, 𝗽𝗹𝗲𝗮𝘀𝗲 𝘃𝗶𝘀𝗶𝘁 𝗼𝘂𝗿 𝘄𝗲𝗯𝘀𝗶𝘁𝗲.

https://www.degruyter.com/journal/key/comp/html#overview