| Evangelos Mitikas is a graduate of Electrical and Electronics Engineering from the University of West Attica (UniWA), Greece. His diploma thesis was titled “Supervised and unsupervised methods in ML and CV using data-driven Log-Det Divergences in the manifold space of SPD covariance matrices”. He is currently an associate researcher at the CONSERT research laboratory at UniWA and at the SoDa research laboratory at UoP, and has been an active volunteer in the IEEE Student Branch for the past three years, holding various council positions. He has expertise in software engineering, web development, and containerization, with research interests focused on cloud computing, machine learning, and computer vision. |
| Evangelos Mitikas is a graduate of Electrical and Electronics Engineering from the University of West Attica (UniWA), Greece. His diploma thesis was titled “Supervised and unsupervised methods in ML and CV using data-driven Log-Det Divergences in the manifold space of SPD covariance matrices”. He is currently an associate researcher at the CONSERT research laboratory at UniWA and at the SoDa research laboratory at UoP, and has been an active volunteer in the IEEE Student Branch for the past three years, holding various council positions. He has expertise in software engineering, web development, and containerization, with research interests focused on cloud computing, machine learning, and computer vision. |
We will present PROVATO, an edge AI and IoT-powered platform for real-time livestock monitoring. The proposed framework enables farmers to track animal health and behaviour, ensuring scalable data processing and AI inference at both the edge and the cloud. This approach supports decision-making, reduces resource waste, and improves animal welfare.
We will present PROVATO, an edge AI and IoT-powered platform for real-time livestock monitoring. The proposed framework enables farmers to track animal health and behaviour, ensuring scalable data processing and AI inference at both the edge and the cloud. This approach supports decision-making, reduces resource waste, and improves animal welfare.
We will present PROVATO, an edge AI and IoT-powered platform for real-time livestock monitoring. The proposed framework enables farmers to track animal health and behaviour, ensuring scalable data processing and AI inference at both the edge and the cloud. This approach supports decision-making, reduces resource waste, and improves animal welfare.
We will present PROVATO, an edge AI and IoT-powered platform for real-time livestock monitoring. The proposed framework enables farmers to track animal health and behaviour, ensuring scalable data processing and AI inference at both the edge and the cloud. This approach supports decision-making, reduces resource waste, and improves animal welfare.
