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A Review of the Transition from Industry 4.0 to Industry 5.0: Unlocking the Potential of TinyML in Industrial IoT Systems

https://doi.org/10.3390/sci8010010
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/978-3-031-06371-8_12openalex-snapshot
Edge AI System Using a Thermal Camera for Industrial Anomaly Detection
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Edge AI Deployment and Stream-Based Time Series Classification Within ARTHUR
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Artificial Intelligence for Safety and Reliability Engineering
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Software survey: VOSviewer, a computer program for bibliometric mapping
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Low-Power Memristor for Neuromorphic Computing: From Materials to Applications
inferredcites →https://doi.org/10.1007/s43621-025-01166-0openalex-snapshot
Industry 5.0 as seen through its academic literature: an investigation using co-word analysis
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Exploring the promising role of internet of things in urban water systems: a comprehensive global analysis of insights, trends, and research priorities
inferredcites →https://doi.org/10.1007/s43926-025-00150-4openalex-snapshot
A systematic review on lightweight security algorithms for a sustainable IoT infrastructure
inferredcites →https://doi.org/10.1016/b978-0-44-322202-3.00008-7openalex-snapshot
Cloud and edge intelligence
inferredcites →https://doi.org/10.1016/b978-0-44-322202-3.00014-2openalex-snapshot
TinyML for 5G networks
inferredcites →https://doi.org/10.1016/b978-0-44-322202-3.00017-8openalex-snapshot
6TiSCH adaptive scheduling for Industrial Internet of Things
inferredcites →https://doi.org/10.1016/j.adhoc.2023.103348openalex-snapshot
A review of on-device machine learning for IoT: An energy perspective
inferredcites →https://doi.org/10.1016/j.asej.2025.103281openalex-snapshot
Safeguarding IoT consumer devices: Deep learning with TinyML driven real-time anomaly detection for predictive maintenance
inferredcites →https://doi.org/10.1016/j.cirpj.2025.05.012openalex-snapshot
Low-cost and non-intrusive human digital twin component for task and navigation tracking through pose estimation
inferredcites →https://doi.org/10.1016/j.compbiomed.2025.109653openalex-snapshot
TinyML and edge intelligence applications in cardiovascular disease: A survey
inferredcites →https://doi.org/10.1016/j.cose.2022.103058openalex-snapshot
Towards secure private and trustworthy human-centric embedded machine learning: An emotion-aware facial recognition case study
inferredcites →https://doi.org/10.1016/j.dcan.2024.03.007openalex-snapshot
Spatiotemporal correlation based self-adaptive pose estimation in complex scenes
inferredcites →https://doi.org/10.1016/j.eswa.2023.122735openalex-snapshot
Deploying an energy efficient, secure & high-speed sidechain-based TinyML model for soil quality monitoring and management in agriculture
inferredcites →https://doi.org/10.1016/j.iot.2022.100670openalex-snapshot
Energy consumption of on-device machine learning models for IoT intrusion detection
inferredcites →https://doi.org/10.1016/j.iot.2023.100736openalex-snapshot
Towards energy-aware tinyML on battery-less IoT devices
inferredcites →https://doi.org/10.1016/j.iot.2024.101063openalex-snapshot
Anomaly detection based on Artificial Intelligence of Things: A Systematic Literature Mapping
inferredcites →https://doi.org/10.1016/j.iot.2024.101153openalex-snapshot
Internet of Intelligent Things: A convergence of embedded systems, edge computing and machine learning
inferredcites →https://doi.org/10.1016/j.iot.2024.101398openalex-snapshot
Securing constrained IoT systems: A lightweight machine learning approach for anomaly detection and prevention
inferredcites →https://doi.org/10.1016/j.iot.2024.101403openalex-snapshot
Combinative model compression approach for enhancing 1D CNN efficiency for EIT-based Hand Gesture Recognition on IoT edge devices
inferredcites →https://doi.org/10.1016/j.iotcps.2023.02.004openalex-snapshot
Edge AI: A survey
inferredcites →https://doi.org/10.1016/j.jksuci.2021.11.019openalex-snapshot
A review on TinyML: State-of-the-art and prospects
inferredcites →https://doi.org/10.1016/j.jksuci.2023.101870openalex-snapshot
Communication and computational resource optimization for Industry 5.0 smart devices empowered by MEC
inferredcites →https://doi.org/10.1016/j.mfglet.2022.08.015openalex-snapshot
From self-aware to self-healing for perpetual manufacturing
inferredcites →https://doi.org/10.1016/j.neucom.2025.130746openalex-snapshot
Emerging trends and strategic opportunities in tiny machine learning: A comprehensive thematic analysis
inferredcites →https://doi.org/10.1016/j.procir.2014.03.115openalex-snapshot
Cyber-physical Production Systems: Roots, Expectations and R&D Challenges
inferredcites →https://doi.org/10.1016/j.rineng.2025.105165openalex-snapshot
Engineering a multi model fallback system for edge devices
inferredcites →https://doi.org/10.1038/s41598-025-98571-2openalex-snapshot
Efficient human activity recognition on edge devices using DeepConv LSTM architectures
inferredcites →https://doi.org/10.1049/pbpc068eopenalex-snapshot
Explainable Artificial Intelligence for Trustworthy Internet of Things
inferredcites →https://doi.org/10.1108/ijieom-04-2025-0070openalex-snapshot
From Industry 4.0 to 5.0: leveraging AI and IoT for sustainable and human-centric operations
inferredcites →https://doi.org/10.1109/access.2022.3188862openalex-snapshot
6TiSCH Low Latency Autonomous Scheduling for Industrial Internet of Things
inferredcites →https://doi.org/10.1109/access.2023.3285596openalex-snapshot
Artificial Intelligence and Biosensors in Healthcare and Its Clinical Relevance: A Review
inferredcites →https://doi.org/10.1109/access.2024.3365349openalex-snapshot
A Machine Learning-Oriented Survey on Tiny Machine Learning
inferredcites →https://doi.org/10.1109/access.2024.3437192openalex-snapshot
On TinyML and Cybersecurity: Electric Vehicle Charging Infrastructure Use Case
inferredcites →https://doi.org/10.1109/access.2024.3503516openalex-snapshot
Optimizing Federated Learning on TinyML Devices for Privacy Protection and Energy Efficiency in IoT Networks
inferredcites →https://doi.org/10.1109/access.2025.3557405openalex-snapshot
Enhancing Predictive Maintenance in Mining Mobile Machinery Through a Hierarchical Inference Network
inferredcites →https://doi.org/10.1109/es64449.2025.11136394openalex-snapshot
Intelligent Bearing System Health Monitoring for Smart Manufacturing Conveyors
inferredcites →https://doi.org/10.1109/iccsc66714.2025.11135279openalex-snapshot
A Survey of Model Compression Techniques for TinyML Applications
inferredcites →https://doi.org/10.1109/iedm45625.2022.10019443openalex-snapshot
Energy-efficient activity-driven computing architectures for edge intelligence
inferredcites →https://doi.org/10.1109/islped58423.2023.10244321openalex-snapshot
A Self-Powered Predictive Maintenance System Based on Piezoelectric Energy Harvesting and TinyML
inferredcites →https://doi.org/10.1109/ithings-greencom-cpscom-smartdata-cybermatics55523.2022.00018openalex-snapshot
On-Device Training of Deep Learning Models on Edge Microcontrollers
inferredcites →https://doi.org/10.1109/jiot.2022.3157532openalex-snapshot
Exploring Scalable, Distributed Real-Time Anomaly Detection for Bridge Health Monitoring
inferredcites →https://doi.org/10.1109/jsac.2021.3118352openalex-snapshot
Optimizing Federated Learning in Distributed Industrial IoT: A Multi-Agent Approach
inferredcites →https://doi.org/10.1109/mie.2017.2649104openalex-snapshot
The Future of Industrial Communication: Automation Networks in the Era of the Internet of Things and Industry 4.0
inferredcites →https://doi.org/10.1109/mn55117.2022.9887747openalex-snapshot
Hand-Arm Vibration Monitoring via Embedded Machine Learning on Low Power Wearable Devices
inferredcites →https://doi.org/10.1109/ojcoms.2024.3373177openalex-snapshot
TinyML Empowered Transfer Learning on the Edge
inferredcites →https://doi.org/10.1109/tce.2024.3475393openalex-snapshot
Energy-Aware Compression and Consumption Algorithms for Efficient TinyML Model Using Aquila Optimization in Industrial IoT
inferredcites →https://doi.org/10.1109/tim.2022.3165816openalex-snapshot
Design and Performance Evaluation of an Ultralow-Power Smart IoT Device With Embedded TinyML for Asset Activity Monitoring
inferredcites →https://doi.org/10.1109/wsc63780.2024.10838750openalex-snapshot
Concept of Digital Twins for Autonomous Manufacturing through Virtual Learning and Commissioning
inferredcites →https://doi.org/10.1136/bmj.n71openalex-snapshot
The PRISMA 2020 statement: an updated guideline for reporting systematic reviews
inferredcites →https://doi.org/10.1145/3583683openalex-snapshot
Intelligence at the Extreme Edge: A Survey on Reformable TinyML
inferredcites →https://doi.org/10.1145/3603171openalex-snapshot
TinyNS: Platform-aware Neurosymbolic Auto Tiny Machine Learning
inferredcites →https://doi.org/10.1145/3661820openalex-snapshot
A Review on the emerging technology of TinyML
inferredcites →https://doi.org/10.1145/3665278openalex-snapshot
On-device Online Learning and Semantic Management of TinyML Systems
inferredcites →https://doi.org/10.1145/3670414openalex-snapshot
CASPER: Context-Aware IoT Anomaly Detection System for Industrial Robotic Arms
inferredcites →https://doi.org/10.1155/2022/7437023openalex-snapshot
Tiny Machine Learning for Resource-Constrained Microcontrollers
inferredcites →https://doi.org/10.1371/journal.pone.0329227openalex-snapshot
An optimized stacking-based TinyML model for attack detection in IoT networks
inferredcites →https://doi.org/10.15388/22-infor505openalex-snapshot
Intelligent and Efficient IoT Through the Cooperation of TinyML and Edge Computing
inferredcites →https://doi.org/10.3390/electronics12071541openalex-snapshot
EMG-Based Dynamic Hand Gesture Recognition Using Edge AI for Human–Robot Interaction
inferredcites →https://doi.org/10.3390/electronics13122322openalex-snapshot
Overview of AI-Models and Tools in Embedded IIoT Applications
inferredcites →https://doi.org/10.3390/electronics13173562openalex-snapshot
Advancements in TinyML: Applications, Limitations, and Impact on IoT Devices
inferredcites →https://doi.org/10.3390/en16052161openalex-snapshot
Local Interpretable Explanations of Energy System Designs
inferredcites →https://doi.org/10.3390/fi14120363openalex-snapshot
TinyML for Ultra-Low Power AI and Large Scale IoT Deployments: A Systematic Review
inferredcites →https://doi.org/10.3390/jmmp9070210openalex-snapshot
Optimising Manufacturing Efficiency: A Data Analytics Solution for Machine Utilisation and Production Insights
inferredcites →https://doi.org/10.3390/jsan10010013openalex-snapshot
Virtualizing AI at the Distributed Edge towards Intelligent IoT Applications
inferredcites →https://doi.org/10.3390/jsan10040060openalex-snapshot
Trends in Intelligent Communication Systems: Review of Standards, Major Research Projects, and Identification of Research Gaps
inferredcites →https://doi.org/10.3390/pr9111910openalex-snapshot
From Human-Human to Human-Machine Cooperation in Manufacturing 4.0
inferredcites →https://doi.org/10.3390/rs16213957openalex-snapshot
Review on Hardware Devices and Software Techniques Enabling Neural Network Inference Onboard Satellites
inferredcites →https://doi.org/10.3390/s21124153openalex-snapshot
An Evolving TinyML Compression Algorithm for IoT Environments Based on Data Eccentricity
inferredcites →https://doi.org/10.3390/s21155218openalex-snapshot
LPWAN and Embedded Machine Learning as Enablers for the Next Generation of Wearable Devices
inferredcites →https://doi.org/10.3390/s23031185openalex-snapshot
Lightweight and Energy-Efficient Deep Learning Accelerator for Real-Time Object Detection on Edge Devices
inferredcites →https://doi.org/10.3390/s23042344openalex-snapshot
An Adaptable and Unsupervised TinyML Anomaly Detection System for Extreme Industrial Environments
inferredcites →https://doi.org/10.3390/s23115074openalex-snapshot
Trends and Challenges in AIoT/IIoT/IoT Implementation
inferredcites →https://doi.org/10.3390/s24227273openalex-snapshot
An Evolving Multivariate Time Series Compression Algorithm for IoT Applications
inferredcites →https://doi.org/10.3390/s24227320openalex-snapshot
Embedding Tree-Based Intrusion Detection System in Smart Thermostats for Enhanced IoT Security
inferredcites →https://doi.org/10.3390/s25061656openalex-snapshot
Design and Implementation of ESP32-Based Edge Computing for Object Detection
inferredcites →https://doi.org/10.3390/s25103191openalex-snapshot
Tiny Machine Learning and On-Device Inference: A Survey of Applications, Challenges, and Future Directions
inferredcites →https://doi.org/10.3390/s25123810openalex-snapshot
Embedded Sensor Data Fusion and TinyML for Real-Time Remaining Useful Life Estimation of UAV Li Polymer Batteries
inferredcites →https://doi.org/10.3390/su11164371openalex-snapshot
Industry 5.0—A Human-Centric Solution
inferredcites →https://doi.org/10.3390/technologies12060081openalex-snapshot
A Survey of Machine Learning in Edge Computing: Techniques, Frameworks, Applications, Issues, and Research Directions
inferredcites →https://doi.org/10.34074/proc.240120openalex-snapshot
The Challenges of TinyML Implementation: A Literature Review
inferredcites →https://doi.org/10.36227/techrxiv.172254372.21002541/v1openalex-snapshot
Efficient Deep Learning Models for Edge IOT Devices - A Review

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1016/j.future.2026.108853openalex-snapshot
Overcoming Digital Twin Blindness: An event-triggered edge–cloud architecture using quantized TinyML
inferred← citeshttps://doi.org/10.1016/j.iot.2026.101899openalex-snapshot
A holistic framework for privacy-preserving and trusted cyber threat intelligence in industry 5.0: A fusion of blockchain and tiny semi-supervised class-incremental learning with catastrophic forgetting mitigation
inferred← citeshttps://doi.org/10.1016/j.jii.2026.101117openalex-snapshot
Information integration for Industry 5.0: A review of IIoT–edge–cloud architectures with 6G/ISAC capabilities
inferred← citeshttps://doi.org/10.1109/iccmc69250.2026.11624758openalex-snapshot
Machine Learning-based Predictive Maintenance for Industrial IoT Devices using Google Cloud AI Platform
inferred← citeshttps://doi.org/10.1109/icetics69505.2026.11651295openalex-snapshot
A Dynamic Trust-Elimination Security Architecture for Sustainable Cyber-Threat Detection in Edge-Based IoT Systems
inferred← citeshttps://doi.org/10.1109/icici68773.2026.11580703openalex-snapshot
Multi-Modal Deep Learning for Early Detection of Human and Plant Diseases using Image and Sensor Data
inferred← citeshttps://doi.org/10.1109/icici68773.2026.11581091openalex-snapshot
AI-Driven Framework for Predicting Human and Plant Diseases Through Image Processing and Wearable Sensors
inferred← citeshttps://doi.org/10.1109/icitsif69060.2026.11608636openalex-snapshot
An Interpretable Intelligence Model for High-Assurance Intrusion Detection in Distributed and Resource-Constrained IoT Ecosystems
inferred← citeshttps://doi.org/10.1109/icsedis68157.2026.11518516openalex-snapshot
A Distributed Learning Framework for Data Privacy and Security in IoT Environments
inferred← citeshttps://doi.org/10.1109/tqcebt67648.2026.11681264openalex-snapshot
A Dynamic Trust-Elimination Security Architecture Using Continuous AI Validation for Sustainable IoT Infrastructures
inferred← citeshttps://doi.org/10.3390/chips5030028openalex-snapshot
A Privacy-Preserving TinyML-Driven IoT Edge Architecture for Low-Latency Smart Sensing and Autonomous AI-Based Control
inferred← citeshttps://doi.org/10.3390/fi18080403openalex-snapshot
Noospheric Technologies in Knowledge-Intensive Socio-Technical Systems: A Conceptual Framework Applied to Science and Education
inferred← citeshttps://doi.org/10.3390/s26082550openalex-snapshot
TinyML in Industrial IoT: A Systematic Review of Applications, System Components, and Methodologies
Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.