Deploying TinyML for energy-efficient object detection and communication in low-power edge AI systems

Ch Madhu Bhushan; Priya Koppuravuri; Nomitha Prasanthi; Firoj Gazi; Md Muzakkir Hussain; Mohammad Abdussami; Aguru Aswani Devi; Jamilurahman Faizi

doi:10.1038/s41598-025-27818-9

Deploying TinyML for energy-efficient object detection and communication in low-power edge AI systems

C Ch Madhu Bhushan P Priya Koppuravuri N Nomitha Prasanthi F Firoj Gazi M Md Muzakkir Hussain M Mohammad Abdussami A Aguru Aswani Devi J Jamilurahman Faizi

Download PDF View Original

APA MLA Chicago BibTeX RIS

Article Details

Journal Scientific Reports

Volume / Issue Vol. 15, Issue 1

Published December 05, 2025

DOI 10.1038/s41598-025-27818-9

ISSN 2045-2322

Publisher Nature Portfolio

Journal Info

Scientific Reports

Nature Portfolio

ISSN: 2045-2322 Open Access Life Sciences

Authors (8)

C

Ch Madhu Bhushan

P

Priya Koppuravuri

N

Nomitha Prasanthi

F

Firoj Gazi

M

Md Muzakkir Hussain

M

Mohammad Abdussami

A

Aguru Aswani Devi

J

Jamilurahman Faizi

Deploying TinyML for energy-efficient object detection and communication in low-power edge AI systems

Article Details

Journal Info

Authors (8)

Related Articles from this Journal

AI models of unstable flow exhibit hallucination

The MCAA-YOLO + XPBI integrated model provides a hybrid intelligent measurement method for predicting the body weight of Hu sheep

Application of iron nano-biofertilizers as a sustainable approach to enhance growth and micronutrient uptake in soybean

Adolescents’ status-dependent public and private conformity to prosocial and antisocial decisions in a public goods game

An explainable hierarchical capsule network framework for supporting expert sensory evaluation of herbal medicines with natural language generation