Spatially Grounded AI for Smart Living Spaces.
Research
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.
2025
Demonstration
2025
Instead of remembering names like "Switch on light no. 3",
"Turn on the light on the TV's right."
Without pre-determined setup, simply say,
"Turn on the light near the AC"
2025
Figure visualises the overall TLX scores mean across 6 dimensions and their standard deviations. (Lower the better)
Dimension wise comparison of NASA TLX scores across 6 dimensions. (Lower the better)
Condition 1: Commercially available Google Home Assistant, Condition 2: Proposed Method, INOT Assistant
A total of fifteen participants were recruited for the study, with ages ranging from 18 to 80 years (Mean: 45.8 years, Median: 49 years, Standard Deviation: 19.08).
The gender distribution included: 8 females (53.3%) and 7 males (46.7%).
2025
Model room where the user case study was conducted for both the conditions. The model room has 4 lights and 1 fan, smart home connectivity enabled.
Reference tasks provided included:
"Switch on the light near the AC."
"Switch on the light above the photo frame."
"Turn on the light on the desk."
"Switch on the leftmost light."
"Turn on the fan."
"Turn on lighting for studying or working."
2025
@article{kalivarathan2025intelligence,
title={Intelligence of Things: A Spatial Context-Aware Control System for Smart Devices},
author={Kalivarathan, Sukanth and Mohamed, Muhmmad Abrar Raja and Ravikumar, Aswathy and Harini, S},
journal={arXiv preprint arXiv:2504.13942},
year={2025}
}