A survey on optimization techniques for edge artificial intelligence (ai)
C Surianarayanan, JJ Lawrence, PR Chelliah… - Sensors, 2023 - mdpi.com
Artificial Intelligence (Al) models are being produced and used to solve a variety of current
and future business and technical problems. Therefore, AI model engineering processes …
and future business and technical problems. Therefore, AI model engineering processes …
Federated learning using game strategies: State-of-the-art and future trends
R Gupta, J Gupta - Computer Networks, 2023 - Elsevier
Federated learning (FL) is a new and promising paradigm that allows devices to learn
without sharing data with the centralized server. It is often built on decentralized data where …
without sharing data with the centralized server. It is often built on decentralized data where …
Energy-Efficient Federated Learning with Resource Allocation for Green IoT Edge Intelligence in B5G
An edge intelligence-aided Internet-of-Things (IoT) network has been proposed to
accelerate the response of IoT services by deploying edge intelligence near IoT devices …
accelerate the response of IoT services by deploying edge intelligence near IoT devices …
Federated Learning based Privacy Ensured Sensor Communication in IoT Networks: A Taxonomy, Threats and Attacks
Our daily lives are significantly impacted by intelligent Internet of Things (IoT) application,
services, IoT gadgets, and more intelligent industries. Artificial Intelligence (AI) is anticipated …
services, IoT gadgets, and more intelligent industries. Artificial Intelligence (AI) is anticipated …
Experimental Evaluation and Analysis of Federated Learning in Edge Computing Environments
Federated learning (FL) is a machine learning system that allows a network of devices to
train a model without centralized data. This characteristic makes FL an ideal choice for …
train a model without centralized data. This characteristic makes FL an ideal choice for …
[HTML][HTML] Validation of High-Availability Model for Edge Devices and IIoT
P Peniak, E Bubeníková, A Kanáliková - Sensors, 2023 - mdpi.com
Competitiveness in industry requires smooth, efficient, and high-quality operation. For some
industrial applications or process control and monitoring applications, it is necessary to …
industrial applications or process control and monitoring applications, it is necessary to …
A privacy-preserving federated learning architecture implementing data ownership and portability on edge end-points
P Mpofu, SH Kembo, M Chimbwanda… - International Journal of …, 2023 - emerald.com
Purpose In response to food supply constraints resulting from coronavirus disease 2019
(COVID-19) restrictions, in the year 2020, the project developed automated household …
(COVID-19) restrictions, in the year 2020, the project developed automated household …
Edge-assisted Federated Learning for Autonomous Vehicle Trajectory Prediction
G La Bruna - 2022 - webthesis.biblio.polito.it
The evolution of cars has always been driven by the aim of making transport safer for
passengers and pedestrians, but also the need to improve the livability of the cities …
passengers and pedestrians, but also the need to improve the livability of the cities …
IEEE Smart Cities IEEE Smart Cities
The enormous advancements in learning techniques over the years in the field of federated
learning have made it possible to collaborate in a distributed way and to provide promising …
learning have made it possible to collaborate in a distributed way and to provide promising …