mlsanityData to 14 Oct 2026

Intelligence of Things: A Spatial Context-Aware Control System for Smart Devices

arXiv 2504.13942 ↗First posted 16 Apr 2025cs.HC cs.AI cs.ETcited by 0

Not on the map. Why?

Abstract (arXiv)

This paper introduces Intelligence of Things (INOT), a novel spatial context-aware control system that enhances smart home automation through intuitive spatial reasoning. Current smart home systems largely rely on device-specific identifiers, limiting user interaction to explicit naming conventions rather than natural spatial references. INOT addresses this limitation through a modular architecture that integrates Vision Language Models with IoT control systems to enable natural language commands with spatial context (e.g., "turn on the light near the window"). The system comprises key components including an Onboarding Inference Engine, Zero-Shot Device Detection, Spatial Topology Inference, and Intent-Based Command Synthesis. A comprehensive user study with 15 participants demonstrated INOT's significant advantages over conventional systems like Google Home Assistant, with users reporting reduced cognitive workload (NASA-TLX scores decreased by an average of 13.17 points), higher ease-of-use ratings, and stronger preference (14 out of 15 participants). By eliminating the need to memorize device identifiers and enabling context-aware spatial commands, INOT represents a significant advancement in creating more intuitive and accessible smart home control systems.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 13 of its 26 references that are in the map. First posted on arXiv 16 Apr 2025.

Builds on

13 of 26 references.

References · 13

  1. 2024GPT-4o System Cardcited by 4,588
  2. 2024Gemini 1.5: Unlocking multimodal understanding across millions of tokens of contextcited by 3,224
  3. 2024SpatialVLM: Endowing Vision-Language Models with Spatial Reasoning Capabilitiescited by 706
  4. 2024IoT-LLM: a framework for enhancing Large Language Model reasoning from real-world sensor datacited by 18
  5. 2023SAGE: Smart home Agent with Grounded Executioncited by 13
  6. 2024Efficient Prompting for LLM-based Generative Internet of Thingscited by 12
  7. 2024When IoT Meet LLMs: Applications and Challengescited by 11
  8. 2023"Get ready for a party": Exploring smarter smart spaces with help from large language modelscited by 10
  9. 2024Integrating Large Language Models with Internet of Things Applicationscited by 7
  10. 2024ROOT: VLM based System for Indoor Scene Understanding and Beyondcited by 6
  11. 2023Improving Vision-and-Language Reasoning via Spatial Relations Modelingcited by 5
  12. 2024IoT Device Labeling Using Large Language Modelscited by 3
1 more
  1. 2024AutoIoT: Automated IoT Platform Using Large Language Modelscited by 3

Built on by

Not cited yet.

Similar, not cited

Close in wording, no citation either way

  1. 2023Sasha: Creative Goal-Oriented Reasoning in Smart Homes with Large Language Models
  2. 2026SMH-Bench: Benchmarking LLM Agents for Environment-Grounded Reasoning and Action in Smart Homes
  3. 2024Thoughtful Things: Building Human-Centric Smart Devices with Small Language Models
  4. 2026TRACE: Temporal Reasoning over Context and Evidence for Activity Recognition in Smart Homes
  5. 2026SCENIC: Semantic-Conditioned Edge-Aware Neural Framework for Structured IoT Command Generation
  6. 2026OmniSmartHome: A Multimodal Reasoning Benchmark for Smart-Home Agents
  7. 2026SHACR: A Graph-Augmented Semi-Autonomous Framework for Multi-Class Conflict Resolution in Smart Home IoT Automation ↗
  8. 2025HomeBench: Evaluating LLMs in Smart Homes with Valid and Invalid Instructions Across Single and Multiple Devices