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

arXiv: https://arxiv.org/abs/2404.12486 · HTML: https://mlsanity.com/paper/2404.12486/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- Builds on 10 of its 29 references that are in the map.
- First posted on arXiv 18 Apr 2024.

## Builds on (most cited first, 10 of 10)

- [Multi-Agent Collaboration: Harnessing the Power of Intelligent LLM Agents](https://mlsanity.com/paper/2306.03314/) (2023)
- [Large Language Models Empowered Autonomous Edge AI for Connected Intelligence](https://mlsanity.com/paper/2307.02779/) (2023)
- [Balancing Autonomy and Alignment: A Multi-Dimensional Taxonomy for Autonomous LLM-powered Multi-Agent Architectures](https://mlsanity.com/paper/2310.03659/) (2023)
- [AI-native Interconnect Framework for Integration of Large Language Model Technologies in 6G Systems](https://mlsanity.com/paper/2311.05842/) (2023)
- [Autonomy and Intelligence in the Computing Continuum: Challenges, Enablers, and Future Directions for Orchestration](https://mlsanity.com/paper/2205.01423/) (2022)
- [The Role of LLMs in Sustainable Smart Cities: Applications, Challenges, and Future Directions](https://mlsanity.com/paper/2402.14596/) (2024)
- [Distributed intelligence on the Edge-to-Cloud Continuum: A systematic literature review](https://mlsanity.com/paper/2205.01081/) (2022)
- [Towards Message Brokers for Generative AI: Survey, Challenges, and Opportunities](https://mlsanity.com/paper/2312.14647/) (2023)
- [How Can AI be Distributed in the Computing Continuum? Introducing the Neural Pub/Sub Paradigm](https://mlsanity.com/paper/2309.02058/) (2023)
- [Follow-Me Cloud: When Cloud Services Follow Mobile Users](https://mlsanity.com/paper/2201.05068/) (2022)

## Built on by (most cited first, 4 of 4)

- [UserCentrix: An Agentic Memory-augmented AI Framework for Smart Spaces](https://mlsanity.com/paper/2505.00472/) (2025)
- [Creation of AI-driven Smart Spaces for Enhanced Indoor Environments -- A Survey](https://mlsanity.com/paper/2412.14708/) (2024)
- [Agentic TinyML for Intent-aware Handover in 6G Wireless Networks](https://mlsanity.com/paper/2508.09147/) (2025)
- [Enabling Cloud-Level Accuracy in Edge AI through IoT Data Preprocessing](https://mlsanity.com/paper/2606.22496/) (2026)

## Abstract (arXiv)

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.