[HTML][HTML] The role of industry 4.0 in advancing sustainability development: A focus review in the United Arab Emirates

A Alhammadi, I Alsyouf, C Semeraro… - Cleaner Engineering and …, 2024 - Elsevier
In recent years, the widespread adoption of Industry 4.0 technologies has significantly
enhanced sustainability performance and addressed environmental concerns for …

A review of on-device machine learning for IoT: An energy perspective

N Tekin, A Aris, A Acar, S Uluagac, VC Gungor - Ad Hoc Networks, 2024 - Elsevier
Recently, there has been a substantial interest in on-device Machine Learning (ML) models
to provide intelligence for the Internet of Things (IoT) applications such as image …

[HTML][HTML] An IoT system using deep learning to classify camera trap images on the edge

I Zualkernan, S Dhou, J Judas, AR Sajun, BR Gomez… - Computers, 2022 - mdpi.com
Camera traps deployed in remote locations provide an effective method for ecologists to
monitor and study wildlife in a non-invasive way. However, current camera traps suffer from …

Evaluating YOLO architectures for detecting road killed endangered Brazilian animals

GS Ferrante, LH Vasconcelos Nakamura, S Sampaio… - Scientific reports, 2024 - nature.com
Wildlife roadkill is a recurring, dangerous problem that affects both humans and animals and
has received increasing attention from environmentalists worldwide. Addressing this …

Improving the generalization of visual classification models across IoT cameras via cross-modal inference and fusion

QL Guan, Y Zheng, L Meng, LQ Dong… - IEEE Internet of Things …, 2023 - ieeexplore.ieee.org
The performance of visual classification models across Internet of Things devices is usually
limited by the changes in local environments, resulted from the diverse appearances of the …

Improving animal monitoring using small unmanned aircraft systems (sUAS) and deep learning networks

M Zhou, JA Elmore, S Samiappan, KO Evans… - Sensors, 2021 - mdpi.com
In recent years, small unmanned aircraft systems (sUAS) have been used widely to monitor
animals because of their customizability, ease of operating, ability to access difficult to …

Evaluating the method reproducibility of deep learning models in biodiversity research

W Ahmed, VK Kommineni, B König-Ries… - PeerJ Computer …, 2025 - peerj.com
Artificial intelligence (AI) is revolutionizing biodiversity research by enabling advanced data
analysis, species identification, and habitats monitoring, thereby enhancing conservation …

Filtering empty camera trap images in embedded systems

F Cunha, EM dos Santos, R Barreto… - Proceedings of the …, 2021 - openaccess.thecvf.com
Monitoring wildlife through camera traps produces a massive amount of images, whose a
significant portion does not contain animals, being later discarded. Embedding deep …

Bag of tricks for long-tail visual recognition of animal species in camera-trap images

F Cunha, EM dos Santos, JG Colonna - Ecological Informatics, 2023 - Elsevier
Camera traps are a method for monitoring wildlife and they collect a large number of
pictures. The number of images collected of each species usually follows a long-tail …

Understanding the state of the Art in Animal detection and classification using computer vision technologies

GS Ferrante, FM Rodrigues… - … Conference on Big …, 2021 - ieeexplore.ieee.org
This work presents the results of a survey through the analysis of studies published between
January 2017 and May 2021, aiming to compose a broader view of the state of the art in the …