Results 101 to 110 of about 2,597 (210)

Understanding mushroom farm environment using TinyML-based monitoring devices

Environmental Research Communications
The optimization of environmental conditions in mushroom cultivation is pivotal for maximizing yield and quality. A Smart Environmental Monitoring System for Mushroom Farms is presented in this paper that makes use of advanced Tiny Machine Learning ...
Segun Adebayo, Halleluyah Oluwatobi Aworinde, Oluranti Olayinka Olufemi, Christian Okechukwu Osueke, Abidemi Emmanuel Adeniyi, Oluwasegun Julius Aroba   +5 more
doaj   +1 more source

Tiny machine learning on the edge: A framework for transfer learning empowered unmanned aerial vehicle assisted smart farming

IET Smart Cities
Emerging technologies are continually redefining the paradigms of smart farming and opening up avenues for more precise and informed farming practices.
Ali M. Hayajneh, Sami A. Aldalahmeh, Feras Alasali, Haitham Al‐Obiedollah, Sayed Ali Zaidi, Des McLernon   +5 more
doaj   +1 more source

A Wearable System for Real-Time Fall Detection on Resource-Constrained Devices

Future Internet
In this study, we propose a wearable fall detection system that combines wearable sensors, TinyML model, and IoT-based communication for real-time monitoring and detection of falls. The system is designed for resource-constrained IoT devices where memory,
Timothy Malche, Govind Murari Upadhyay, Sumegh Tharewal, Vipin Balyan, Vikash Kumar Mishra, Gunjan Gupta, Pramod Kumar Soni   +6 more
doaj   +1 more source

TinyWolf — Efficient on-device TinyML training for IoT using enhanced Grey Wolf Optimization [PDF]

Training a deep learning model generally requires a huge amount of memory and processing power. Once trained, the learned model can make predictions very fast with very little resource consumption. The learned weights can be fitted into a microcontroller
Adhikary, Subhrangshu, Dutta, Subhayu, Dwivedi, Ashutosh Dhar   +2 more
core   +1 more source

Wet TinyML: Chemical Neural Network Using Gene Regulation and Cell Plasticity

In our earlier work, we introduced the concept of Gene Regulatory Neural Network (GRNN), which utilizes natural neural network-like structures inherent in biological cells to perform computing tasks using chemical inputs.
Balasubramaniam, Sasitharan, Liò, Pietro, Ratwatte, Adrian, Somathilaka, Samitha, Srisa-an, Witawas, Vuran, Mehmet Can   +5 more
core  

Unveiling the Potential of Tiny Machine Learning for Enhanced People Counting in UWB Radar Data [PDF]

Tiny Machine Learning (TinyML) allows to move the intelligence processing as close as possible to where data are generated, hence reducing the latency with which a decision is made and being able to process data even when remote connection is scarce or ...
Caltabiano, Armando, Navarro, Luis González, Pavan, Massimo, Roveri, Manuel   +3 more
core   +1 more source

Expanding Applications of TinyML in Versatile Assistive Devices: From Navigation Assistance to Health Monitoring System Using Optimized NASNet-XGBoost Transfer Learning

IEEE Access
The healthcare sector receives a considerable amount of unprocessed data from wearable and portable devices. However, traditional cloud-based models used to handle this type of data can pose risks such as exposing sensitive patient data to a network ...
Sreenu Ponnada, Tan Kuan Tak, Pravin R. Kshirsagar, P. Srinivasa Rao, Abhinav Dayal   +4 more
doaj   +1 more source

Simulating Battery-Powered TinyML Systems Optimised using Reinforcement Learning in Image-Based Anomaly Detection

Advances in Tiny Machine Learning (TinyML) have bolstered the creation of smart industry solutions, including smart agriculture, healthcare and smart cities.
Nixon, Ken J., Ping, Jared M.
core  

Real-Time RSSI-Based Indoor Localization Using a Two-Stage TinyML Architecture on Edge Devices

IEEE Access
Indoor positioning is a critical component of navigation and control in automated guided vehicles (AGVs) and autonomous mobile robots (AMRs). Wi-Fi RSSI-based localization provides a cost-effective solution for indoor environments; however, its ...
Ahmet Gurkan Yuksek
doaj   +1 more source

Empowering IoT security: deploying TinyML ensemble techniques for cyberattack detection

Scientific African
As the Internet of Things (IoT) grows and devices connect, protecting IoT networks from vulnerabilities is crucial. Intrusion detection systems (IDS) that use machine learning (ML) techniques are vital for increasing security and preventing unauthorized ...
Abderahmane Hamdouchi, Ali Idri
doaj   +1 more source