A comprehensive survey on tinyml

Y Abadade, A Temouden, H Bamoumen… - IEEE …, 2023 - ieeexplore.ieee.org
Recent spectacular progress in computational technologies has led to an unprecedented
boom in the field of Artificial Intelligence (AI). AI is now used in a plethora of research areas …

TinyML for ultra-low power AI and large scale IoT deployments: A systematic review

N Schizas, A Karras, C Karras, S Sioutas - Future Internet, 2022 - mdpi.com
The rapid emergence of low-power embedded devices and modern machine learning (ML)
algorithms has created a new Internet of Things (IoT) era where lightweight ML frameworks …

How tinyml can be leveraged to solve environmental problems: A survey

H Bamoumen, A Temouden… - … on Innovation and …, 2022 - ieeexplore.ieee.org
Internet of things (IoT) enables the integration of smart and intelligent systems in our lives,
subsequently creating an AI-powered society, where the latter is a substantial ingredient in …

AI-Aided Robotic Wide-Range Water Quality Monitoring System.

A Awwad, GA Husseini… - Sustainability (2071-1050 …, 2024 - search.ebscohost.com
Waterborne illnesses lead to millions of fatalities worldwide each year, particularly in
developing nations. In this paper, we introduce a comprehensive system designed for the …

Integrating Analog PIR Sensor Telemetry with TinyML Inference for On-The-Edge Classification of Moving Objects

RM Umutoni, M Ogore, D Hanyurwimfura… - … Congress on Information …, 2023 - Springer
Identification of moving objects plays an important role in different real-time applications
such as security monitoring, social distancing for infection disease spreading surveillance …

Improving edge AI for industrial IoT applications with distributed learning using consensus

S Fidelis, M Castro, F Siqueira - Design Automation for Embedded …, 2024 - Springer
Abstract Internet of Things (IoT) devices produce massive amounts of data in a very short
time. Transferring these data to the cloud to be analyzed may be prohibitive for applications …

HW/SW Collaborative Techniques for Accelerating TinyML Inference Time at No Cost

B Sun, M Hassan - 2024 27th Euromicro Conference on Digital …, 2024 - ieeexplore.ieee.org
With the unprecedented boom in TinyML development, optimizing Artificial Intelligence (AI)
inference on resource-constrained microcontrollers (M CU s) is of paramount importance …

Condition Monitoring of Oil-immersed Transformers Using AI Edge Inference for Incipient Fault Prediction: A case study

GY Odongo, R Musabe… - 2022 IEEE PES/IAS …, 2022 - ieeexplore.ieee.org
The question of transformer dependability and reliability remains a salient feature in
determining the stability of the power supply system. Transformers are amongst the most …

Integrating analog PIR sensing with TinyML inference for on-the-edge classification of moving objects

MR UMUTONI - 2022 - dr.ur.ac.rw
Classification of moving objects plays an important role in different real-life applications,
especially for security monitoring. Digital Passive InfraRed (PIR) devices are the most used …