We gratefully acknowledge support from
the Simons Foundation and member institutions.
Full-text links:

Download:

Current browse context:

cs.DC

Change to browse by:

References & Citations

DBLP - CS Bibliography

Bookmark

(what is this?)
CiteULike logo BibSonomy logo Mendeley logo del.icio.us logo Digg logo Reddit logo

Computer Science > Distributed, Parallel, and Cluster Computing

Title: Follow-Me AI: Energy-Efficient User Interaction with Smart Environments

Abstract: This article introduces Follow-Me AI, a concept designed to enhance user interactions with smart environments, optimize energy use, and provide better control over data captured by these environments. Through AI agents that accompany users, Follow-Me AI negotiates data management based on user consent, aligns environmental controls as well as user communication and computes resources available in the environment with user preferences, and predicts user behavior to proactively adjust the smart environment. The manuscript illustrates this concept with a detailed example of Follow-Me AI in a smart campus setting, detailing the interactions with the building's management system for optimal comfort and efficiency. Finally, this article looks into the challenges and opportunities related to Follow-Me AI.
Subjects: Distributed, Parallel, and Cluster Computing (cs.DC); Artificial Intelligence (cs.AI); Emerging Technologies (cs.ET); Machine Learning (cs.LG)
Cite as: arXiv:2404.12486 [cs.DC]
  (or arXiv:2404.12486v2 [cs.DC] for this version)

Submission history

From: Alaa Saleh [view email]
[v1] Thu, 18 Apr 2024 20:00:25 GMT (2334kb,D)
[v2] Mon, 22 Apr 2024 19:20:33 GMT (2334kb,D)

Link back to: arXiv, form interface, contact.