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

Alaa Saleh, Praveen Kumar Donta, Roberto Morabito, Naser Hossein Motlagh, Lauri Lovén

TL;DR

Follow-Me AI addresses the challenge of energy-efficient, privacy-conscious human interaction with smart environments by introducing AI agents that accompany users and negotiate data management, coordinate environmental controls, and predict user behavior across a device-edge-cloud continuum. The approach leverages an AI interconnect fabric and multi-agent coordination, underpinned by LLMs and GenAI, to deliver context-aware, proactive adjustments while balancing latency, energy use, and data governance. A detailed smart campus case study demonstrates integration with building management to tailor room conditions and network resources, achieving comfort and efficiency gains. The paper also identifies open challenges and research questions in orchestration, mobility, QoS/QoE, and LLMOps, outlining a path toward scalable, personalized, and sustainable intelligent 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.

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

TL;DR

Follow-Me AI addresses the challenge of energy-efficient, privacy-conscious human interaction with smart environments by introducing AI agents that accompany users and negotiate data management, coordinate environmental controls, and predict user behavior across a device-edge-cloud continuum. The approach leverages an AI interconnect fabric and multi-agent coordination, underpinned by LLMs and GenAI, to deliver context-aware, proactive adjustments while balancing latency, energy use, and data governance. A detailed smart campus case study demonstrates integration with building management to tailor room conditions and network resources, achieving comfort and efficiency gains. The paper also identifies open challenges and research questions in orchestration, mobility, QoS/QoE, and LLMOps, outlining a path toward scalable, personalized, and sustainable intelligent 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.
Paper Structure (20 sections, 3 figures, 1 table)

This paper contains 20 sections, 3 figures, 1 table.

Table of Contents

  1. Interaction with a Smart Building
  2. From Follow-Me Cloud to Follow-Me AI
  3. STATE-OF-THE-ART
  4. Smart Environments
  5. Computing Continuum
  6. AI Interconnect
  7. Large Language Models (LLMs)
  8. FOLLOW-ME AI
  9. Overview
  10. Architectural overview
  11. Benefits
  12. CASE STUDY
  13. Experimental Scenario on the Smart Campus.
  14. Data Flow and Interaction.
  15. Monitoring and Feedback.
  16. ...and 5 more sections

Figures (3)

  • Figure 1: Follow-Me AI for smart building interaction.
  • Figure 2: Follow-Me AI Architectural Layers.
  • Figure 3: Interaction diagram showing the data flow and agent collaboration within the smart campus environment, highlighting the roles of the Smartphone Agent, Central Coordination Agent, and Smart Building Agent in optimizing room conditions and device settings.