Artificial Intelligence in the IoT Era: A Review of Edge AI Hardware and Software

Scikit-learn: Machine Learning in Python

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Scoping studies: advancing the methodology

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Convergence of Edge Computing and Deep Learning: A Comprehensive Survey

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Edge Intelligence: The Confluence of Edge Computing and Artificial Intelligence

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Fog Computing: Platform and Applications

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To prune, or not to prune: exploring the efficacy of pruning for model compression

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Edge Machine Learning for AI-Enabled IoT Devices: A Review

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Communication-efficient edge ai: algorithms and systems

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A review on TinyML: State-of-the-art and prospects

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AI Benchmark: Running Deep Neural Networks on Android Smartphones

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CMSIS-NN: Efficient Neural Network Kernels for Arm Cortex-M CPUsPreprint

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AI Benchmark: All About Deep Learning on Smartphones in 2019

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Real-time apple detection system using embedded systems with hardware accelerators: an edge ai application

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Making knowledge tradable in edge-ai enabled iot: a consortium blockchain-based efficient and incentive approach

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Glow: Graph Lowering Compiler Techniques for Neural NetworksPreprint

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Survey of Machine Learning Accelerators

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Edge-AI in LoRa-based Health Monitoring: Fall Detection System with Fog Computing and LSTM Recurrent Neural Networks

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DeepEdgeBench: Benchmarking deep neural networks on edge devices

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TVM: End-to-End Optimization Stack for Deep LearningPreprint

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Machine Learning on Mainstream Microcontrollers

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Techology trend of edge AI

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OpenVINO Deep Learning Workbench: Comprehensive Analysis and Tuning of Neural Networks Inference

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HierTrain: Fast Hierarchical Edge AI Learning With Hybrid Parallelism in Mobile-Edge-Cloud Computing

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ONNC: A Compilation Framework Connecting ONNX to Proprietary Deep Learning Accelerators

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Cluster Pruning: An Efficient Filter Pruning Method for Edge AI Vision Applications

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A Survey of AI Accelerators for Edge Environment

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Trustworthy Target Tracking With Collaborative Deep Reinforcement Learning in EdgeAI-Aided IoT

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Towards security and privacy for edge ai in iot/ioe based digital marketing environments

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AntiConcealer: Reliable Detection of Adversary Concealed Behaviors in EdgeAI-Assisted IoT

Zhang, J., Bhuiyan, M. Z. A., Xu, Y., Wang, T., Xu, X., Hayajneh, T. S., & Khan, F. (2021) · IEEE Internet of Things Journal · doi:10.1109/jiot.2021.3103138 · Cited by 49 · see citing works

Federated K-Means Clustering: A Novel Edge AI Based Approach for Privacy Preservation

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A Hardware Acceleration Platform for AI-Based Inference at the Edge

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emlearn/emlearn: 0.17.1

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emlearn: Machine Learning inference engine for Microcontrollers and Embedded Devices

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Edge ai and blockchain for privacy-critical and data-sensitive applications

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Literature Review of Deep Network Compression

Alqahtani, A., Xie, X., & Jones, M. W. (2021) · Informatics · doi:10.3390/informatics8040077 · Cited by 38 · see citing works

EdgeAl: A Vision for Deep Learning in the IoT Era

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Res6Edge: An Edge-AI Enabled Resource Sharing Scheme for C-V2X Communications towards 6G

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Edge AI-based Respiratory Disease Recognition from Exhaled Breath Signatures

Ooko, S. O., Mukanyiligira, D., Munyampundu, J. P., & Nsenga, J. (2021) · IEEE Jordan International Joint Conference on Electrical Engineering and Information Technology (JEEIT) · doi:10.1109/jeeit53412.2021.9634140 · Cited by 19 · see citing works

EmbML Tool: Supporting the use of Supervised Learning Algorithms in Low-Cost Embedded Systems

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Synthetic Exhaled Breath Data-Based Edge AI Model for the Prediction of Chronic Obstructive Pulmonary Disease

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Leveraging Artificial Intelligence of Things for Anomaly Detection in Advanced Metering Infrastructures

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Performance Enhancement of Edge-AI-Inference Using Commodity MRAM: IoT Case Study

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Embedded machine learning-based data reduction in application-specific constrained IoT networks

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Functionality Enhanced Memories for Edge-AI Embedded Systems

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Data Collection and Utilization Framework for Edge AI Applications

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NeuroPilot: A Cross-Platform Framework for Edge-AI

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A two-stage-pipeline CPU of SH-2 architecture implemented on FPGA and SoC for IoT, edge AI and robotic applications

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A higher-level Neural Network library on Microcontrollers (NNoM)

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EdgeAI: Diabetic Retinopathy Detection in Intel Architecture

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Object Search Using Edge-AI Based Mobile Robot

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Heterogeneous Computing for Edge AI

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A C Code Generator for Fast Inference and Simple Deployment of Convolutional Neural Networks on Resource Constrained Systems

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A CNN-Based Human Head Detection Algorithm Implemented on Edge AI Chip

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Compiler Toolchains for Deep Learning Workloads on Embedded PlatformsPreprint

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Intelligent Acoustic Module for Autonomous Vehicles using Fast Gated Recurrent approach

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MRAM-based BER resilient Quantized edge-AI Networks for Harsh Industrial Conditions

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Edge AI: A survey

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Empowering Edge Intelligence: A Comprehensive Survey on On-Device AI Models

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Edge deep learning in computer vision and medical diagnostics: a comprehensive survey

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A survey on optimization techniques for edge artificial intelligence (ai)

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Towards autonomous mapping in agriculture: A review of supportive technologies for ground robotics

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Edge AI for Internet of Energy: Challenges and perspectives

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A Survey on Edge Computing (EC) Security Challenges: Classification, Threats, and Mitigation Strategies

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Disclosing Edge Intelligence: A Systematic Meta-Survey

Barbuto, V., Savaglio, C., Chen, M., & Fortino, G. (2023) · Big Data and Cognitive Computing · doi:10.3390/bdcc7010044 · Cited by 65 · see citing works

Design, Implementation, and Practical Evaluation of a Voice Recognition Based IoT Home Automation System for Low-Resource Languages and Resource-Constrained Edge IoT Devices: A System for Galician and Mobile Opportunistic Scenarios

Froiz-Míguez, I., Fraga‐Lamas, P., & Fernández‐Caramés, T. M. (2023) · IEEE Access · doi:10.1109/access.2023.3286391 · Cited by 58 · see citing works

Influence of Smart Sensors on Structural Health Monitoring Systems and Future Asset Management Practices

Preethichandra, D. M. G., Suntharavadivel, T. G., Kalutara, P., Piyathilaka, L., & Izhar, U. (2023) · Sensors · doi:10.3390/s23198279 · Cited by 55 · see citing works

LAERACE: Taking the policy fast-track towards low-altitude economy

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A collective AI via lifelong learning and sharing at the edge

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Edge AI: A Comprehensive Survey of Technologies, Applications, and Challenges

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The Many Faces of Edge Intelligence

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Analysing Edge Computing Devices for the Deployment of Embedded AI

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Machine Learning for Evaluating Hospital Mobility: An Italian Case Study

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Continual and wisdom learning for federated learning: A comprehensive framework for robustness and debiasing

Iqbal, S., Zhong, X., Khan, M. A., Wu, Z., AlHammadi, D. A., Liu, W., & Choudhry, I. A. (2025) · Information Processing & Management · doi:10.1016/j.ipm.2025.104157 · Cited by 24 · see citing works

Tiny Machine Learning Battery State-of-Charge Estimation Hardware Accelerated

Pau, D. P., & Aniballi, A. (2024) · Applied Sciences · doi:10.3390/app14146240 · Cited by 22 · see citing works

Artificial Intelligence for DC Arc Fault Detection in Photovoltaic Systems: A Comprehensive Review

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Benchmarking Energy and Latency in TinyML: A Novel Method for Resource-Constrained AI

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AgTech: A Survey on Digital Twins Based Aquaculture Systems

Le, N.-B.-V., Woo, H., Lee, D., & Huh, J. (2024) · IEEE Access · doi:10.1109/access.2024.3443859 · Cited by 20 · see citing works

Enabling edge-driven Dataspace integration through convergence of distributed technologies

Singh, P., Beliatis, M. J., & Presser, M. A. (2024) · Internet of Things · doi:10.1016/j.iot.2024.101087 · Cited by 18 · see citing works

Artificial Intelligence-Enhanced Wearable Blood Pressure Monitoring in Resource-Limited Settings: A Co-Design of Sensors, Model, and Deployment

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Evaluation and Selection of Hardware and AI Models for Edge Applications: A Method and A Case Study on UAVs

Şahin, M. C., & Tarhan, A. (2025) · Applied Sciences · doi:10.3390/app15031026 · Cited by 15 · see citing works

Integration of artificial intelligence with a customized Four-Probe station for I-V characteristic classification and prediction

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Soft sensory-neuromorphic system for closed-loop neuroprostheses

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The Role of Artificial Intelligence in Boosting Cybersecurity and Trusted Embedded Systems Performance: A Systematic Review on Current and Future Trends

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Animal-borne soundscape logger as a system for edge classification of sound sources and data transmission for monitoring near-real-time underwater soundscape

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Smart Lighting Systems: State-of-the-Art in the Adoption of the EdgeML Computing Paradigm

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Edge Artificial Intelligence in Large-Scale IoT Systems, Applications, and Big Data Infrastructures

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Low-rank adaptation for edge AI

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A LIGHTWEIGHT MULTI-PERSON POSE ESTIMATION SCHEME BASED ON JETSON NANO

Liu, L., Blancaflor, E., & Abisado, M. (2023) · Applied Computer Science · doi:10.35784/acs-2023-01 · Cited by 7 · see citing works

Research on High-Performance Fourier Transform Algorithms Based on the NPU

Li, Q., Zuo, D., Feng, Y., & Wen, D. (2024) · Applied Sciences · doi:10.3390/app14010405 · Cited by 7 · see citing works

Hardware Acceleration and Approximation of CNN Computations: Case Study on an Integer Version of LeNet

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Assessing the Impact of Sampling Irregularity in Time Series Data: Human Activity Recognition As A Case Study

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Co-Design of Lightweight Neural Network and Low-Power Edge Computing Architecture for Intelligent Electronic Nose System

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Edge Intelligence Expanding BI Architectures Beyond the Cloud

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Federated Edge AI for Adaptive Zero-Trust Security in Resource-Constrained IoT Networks

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Advancing Edge Artificial Intelligence

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Advancing Edge Artificial Intelligence

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Practical Evaluation of Federated Learning in Edge AI for IoT

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IoT based Fish Farming Management

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Edge AI Trustworthiness: Revisiting Bit-Flip Impacts and Criticality Conditions

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A Multi-Teacher Knowledge Distillation Framework with Aggregation Techniques for Lightweight Deep Models

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Examination of TinyML Approach in ESP32-Based NFC Applications

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A Scalable External Memory Access and On-Chip Storage Architecture for Edge-AI Accelerators : – Multi-Path Rolling Data Refresh and Layer-Wise Bank Allocation –

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Edge Intelligence in the IoT Era: A Review of Architectural Paradigms

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A TinyML-Based IoT Device for Advanced Shipping Monitoring

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Edge-Optimized AI Architecture: MRAM-Based Near Memory Computing Macro Balancing Between Memory Capacity and Computation

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A Tiny Processor with Rapid Interrupt Response for AI Accelerator Control

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Edge AI Lifecycle Management

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Performance Scaling of Silicon after Moore’s LawPreprint

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Enhancing Critical Infrastructure Cybersecurity: Collaborative Dnn Synthesis in the Cloud ContinuumPreprint

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Board 393: Supporting Hardware Engineering Career Choice in First-Year Engineering Students

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Development of IoT Multilingual Voice Controlled Home Automation System

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Application analysis and future development of AI hardware acceleration period

Hu, J. (2024) · Highlights in Science Engineering and Technology · doi:10.54097/1b96k506

ASFRM: An Array State Self-feedback-Based Self-reconfiguration Mechanism in a Reconfigurable Array Processor

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Model Compression in Low Performance Edge Computing

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A Novel Approach for Restoring Lost Details in Pore Network Images based on Pattern Recognition using Generative Adversarial Networks

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An End-to-End Flow to Deploy and Accelerate TinyML Mixed-Precision Models on RISC-V MCUsPreprint

Manca, E., Urbinati, L., & Casu, M. R. (2025) · doi:10.36227/techrxiv.173161032.20267860/v3

A Survey of the State-of-the-Art Compilers and Benchmarks for Embedded Systems

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Sustainable Sericulture - A Pillar of Modern Agriculture

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Efficient Adversarial Detection Frameworks for Vehicle-to-Microgrid Services in Edge Computing

Omara, A., & Kantarcı, B. (2025) · IEEE International Conference on Communications workshops · doi:10.1109/iccworkshops67674.2025.11162172

Development Of Smart Energy Monitoring Internet of Things System Based on App Inventor for Electric Energy Efficiency

Pancane, I. W. D., Adrama, I. N. G., & Sutama, I. W. (2025) · Advance Sustainable Science Engineering and Technology · doi:10.26877/asset.v7i4.2006

Accelerating Mixed-Precision QNN Inference on RISC-V MCUs With the STAR-MAC Unit

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DC-DC Converter Optimization Strategies for Improved Performance with Resistive Loads in Low-Power Applications

Elakkad, S., Abdellatif, S. O., Ismail, A. H., & Ghali, H. A. (2025) · doi:10.1109/icm66518.2025.11322456

Integrated Photonics for Neuromorphic Computing

Meyer, L., Xu, R., & Pernice, W. H. P. (2026) · Machine intelligence for materials science · doi:10.1007/978-3-032-04129-6_17

TinyML-Based Hazardous Gas Detection for Intelligent Personal Protective Equipment

Kudrin-Gusten, C., Kühl, M., Barth, V., & Yu, H. (2025) · IEEE International Conference on Metrology for eXtended Reality, Artificial Intelligence and Neural Engineering (MetroXRAINE) · doi:10.1109/metroxraine66377.2025.11340490

A Study on the Development of a Multimodal Daily Life Support App for People with Visual Impairment

Jeon, J., Lee, Y., Kim, K., Choi, J., & Yoo, S. (2026) · The Journal of Korean Association of Computer Education · doi:10.32431/kace.2026.29.3.004

Edge devices and platforms for embedded artificial intelligence

Mellit, A., Hajji, B., & Baghli, L. (2026) · Elsevier eBooks · doi:10.1016/b978-0-443-44835-5.00003-5

Edge AI: Embedded Intelligence, a Review on Hardware and Applications

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The Global Value Chain of Edge Artificial Intelligence: a technological and strategic perspective

Muciaccia, T., & Tedeschi, P. (2026) · Business Technology & Innovation Studies Journal · doi:10.66578/btis.v2i3.37

Open-Source Edge AI Systems in Practice: An Empirical Study of Architectural Characteristics

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A First Look at Multimodal Mobile Application Performance on XR and AI Smart Glasses

Khalaf, M., Garcia, M., Chadha, M., & Dasari, M. (2026) · ACM Annual International Conference on Mobile Computing and Networking (MobiCom) · doi:10.1145/3795866.3844477

Edge-based artificial intelligence: Understanding the evolution of hardware and software and future trends

Khan, T. M., Haq, Q. E. U., Iqbal, S., & Soomro, T. A. (2026) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2026.114526 · Cited by 4 · see citing works

A Survey of AI Accelerators for Edge Environment

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Computational intelligence enabled hardware software co design for energy efficient Edge Artificial Intelligence

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Edge AI: Embedded Intelligence, a Review on Hardware and Applications

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Edge AI: A survey

Singh, R., & Gill, S. S. (2023) · Internet of Things and Cyber-Physical Systems · doi:10.1016/j.iotcps.2023.02.004 · Cited by 572 · see citing works