AI and ML-driven deployment and optimization in wireless sensor networks
AI and machine learning (ML) technologies are revolutionizing the deployment and optimization of wireless sensor networks (WSNs). These advanced techniques enable the efficient placement and management of sensor nodes, enhancing network coverage, energy efficiency, and data accuracy. Studies explore methods like federated learning, which allows distributed model training across sensor nodes, while preserving data privacy. Using these AI or ML-driven approaches aids in developing robust and scalable WSNs that can adapt to dynamic environments and support various applications, from smart cities to environmental monitoring.
This Collection calls for submissions of original research into techniques that help to develop and deploy strategies of AI or ML-driven design for wireless sensor networks, contributing to the advancement of intelligent and efficient network systems.
Submitting a paper for consideration
To submit your manuscript for consideration at Scientific Reports as part of this Collection, please follow the steps detailed on this page. On the first page of our online submission system, under “I’m submitting:” select the option “A research article”. Under the “Details” tab, authors should select the Collection title: “AI and ML-driven deployment and optimization in wireless sensor networks” from the drop-down option. Authors should express their interest in the Collection in their cover letter.
Accepted papers are published on a rolling basis as soon as they are ready.
In addition to papers on AI and ML-driven deployment and optimization in wireless sensor networks, Scientific Reports welcomes all original research in the field of Physical Sciences. To browse our latest articles in Physical Sciences click here.