Intelligent task-oriented semantic communication method in artificial intelligence of things by Chuanhong LIU, Caili GUO, Yang YANG, Chunyan FENG, Qizheng SUN, Jiujiu CHEN

“…With the integration and development of Internet of things (IoT) and artificial intelligence (AI) technologies, traditional data centralized cloud computing processing methods are difficult to effectively remove a large amount of redundant information in data, which brings challenges to the low-latency and high-precision requirements of intelligent tasks in the artificial intelligence of things (AIoT).In response to this challenge, a semantic communication method oriented to intelligent tasks in AIoT was proposed based on the deep learning method.For image classification tasks, convolutional neural networks (CNN) were used on IoT devices to extract image feature maps.Starting from semantic concepts, semantic concepts and feature maps were associated to extract semantic relationships.Based on the semantic relationships, semantic compression was implemented to reduce the pressure of network transmission and the processing delay of intelligent tasks.Experimental and simulation results show that, compared with traditional communication scheme, the proposed method is only about 0.8% of the traditional scheme, and at the same time it has higher classification task performance.Compared with the scheme that all feature maps are transmitted, the transmission delay of the proposed method is reduced by 80% and the effective accuracy of image classification task is greatly improved.…”
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Double layer federated security learning architecture for artificial intelligence of things by ZHENG Chengbo, YAN Haonan, FU Caili, ZHANG Dong, LI Hui, WANG Bin

Subjects: “…artificial intelligence of things…”
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Fostering student competencies and perceptions through artificial intelligence of things educational platform by Sasithorn Chookaew, Pornchai Kitcharoen, Suppachai Howimanporn, Patcharin Panjaburee

“…These institutions have been actively developing teaching methods that enhance practical AI applications, particularly through integrating AI with the Internet of Things (IoT), leading to the emergence of the Artificial Intelligence of Things (AIoT). This convergence promises significant advancements in AI education, addressing gaps in structured learning methods for AIoT. …”
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Assuring assistance to healthcare and medicine: Internet of Things, Artificial Intelligence, and Artificial Intelligence of Things by Poshan Belbase, Rajan Bhusal, Sapana Sharma Ghimire, Shreesti Sharma, Bibek Banskota

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AIoT-Based Visual Anomaly Detection in Photovoltaic Sequence Data via Sequence Learning by Qian Wei, Hongjun Sun, Jingjing Fan, Guojun Li, Zhiguang Zhou

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Multimodal Federated Learning in AIoT Systems: Existing Solutions, Applications, and Challenges by Christos Anagnostopoulos, Alexandros Gkillas, Christos Mavrokefalidis, Erion-Vasilis Pikoulis, Nikos Piperigkos, Aris S. Lalos

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RETRACTED: Assisting Smart Construction With Reliable Edge Computing Technology by Qiang Yue, Song Mu, Longguan Zhang, Zhun Wang, Zhun Wang, Zhonghua Zhang, Xing Zhang, Yongge Wang, Yongge Wang, Zhuang Miao, Zhuang Miao

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Integration of Foundation Models and Federated Learning in AIoT-Based Aircraft Health Monitoring Systems by Igor Kabashkin

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Attack-detection and multi-clock source cooperation-based accurate time synchronization for PLC-AIoT in smart parks by Zhigang Du, Sunxuan Zhang, Zijia Yao, Zhenyu Zhou, Muhammad Tariq

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A Flexible, Large-Scale Sensing Array with Low-Power In-Sensor Intelligence by Zhangyu Xu, Fan Zhang, Erxuan Xie, Chao Hou, Liting Yin, Hanqing Liu, Mengfei Yin, Lang Yin, Xuejun Liu, YongAn Huang

“…Artificial intelligence of things systems equipped with flexible sensors can autonomously and intelligently detect the condition of the surroundings. …”
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AIoT: a taxonomy, review and future directions by Jiyi WU, Wenjuan LI, Jian CAO, Shiyou QIAN, Qifei ZHANG, Rajkumar BUYYA

“…AIoT (artificial intelligence of things) is an integrated product of artificial intelligence (AI) and internet of things (IoT).Currently, it has been widely used in smart cities, smart homes, smart manufacturing, and driverless.However, the research of AIoT is still in its infancy, facing with many problems and challenges.In order to clarify the concept and provide possible solutions, a comprehensive survey was carried out on AIoT.Firstly, a clear definition of AIoT was provided, along with the brief introduction on its background and application scenarios.And then a novel cloud-edge-end hybrid AIoT architecture for intelligent information processing was constructed.Based on the research framework of AIoT, the research status and solutions were discussed, including AI integrated IoT data acquisition, complex event processing and coordination, cloud-edge-end integration, AI-enhanced IoT security and privacy, and AI-based applications, etc.Finally, it identified the open challenges and offers future research directions.…”
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Decoupled Time-Dimensional Progressive Self-Distillation With Knowledge Calibration for Edge Computing-Enabled AIoT by Yingchao Wang, Wenqi Niu, Hanpo Hou

“…This enables model self-augmentation without the need for large teacher models, making it particularly suitable for resource-constrained edge and fog computing environments within the Artificial Intelligence of Things (AIoT). However, the confidence in the historical model is often insufficient, and its output exists at a higher semantic level. …”
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Efficient Implementation of Mahalanobis Distance on Ferroelectric FinFET Crossbar for Outlier Detection by Musaib Rafiq, Yogesh Singh Chauhan, Shubham Sahay

“…The developments in the nascent field of artificial-intelligence-of-things (AIoT) relies heavily on the availability of high-quality multi-dimensional data. …”
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