Sherlock: automatically locating objects for humans

  • Authors:
  • Aditya Nemmaluri;Mark D. Corner;Prashant Shenoy

  • Affiliations:
  • UMass Amherst, Amherst, MA, USA;UMass Amherst, Amherst, MA, USA;UMass Amherst, Amherst, MA, USA

  • Venue:
  • Proceedings of the 6th international conference on Mobile systems, applications, and services
  • Year:
  • 2008

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Abstract

Over the course of a day a human interacts with tens or hundreds of individual objects. Many of these articles are nomadic, relying on human memory to manually index, inventory, organize, search, and locate them. However, Radio Frequency Identification (RFID) tags hold great promise for automating these tasks. While originally envisioned for managing supply chains and store inventories, RFID tags support the properties necessary for helping humans to manage their objects. This paper presents Sherlock, a system that leverages RFID tags for human-object interaction. Sherlock combines concepts from sensors, radar technology, and computer graphics to implement a novel localization and visualization system for everyday objects. At the heart of Sherlock is a new RFID localization technique that uses steerable antennas to sweep a room, discovering, localizing and indexing tagged objects. In response to user queries, Sherlock displays the locations of matching objects using images from a video camera. We have implemented a prototype of Sherlock to conduct experiments in a real office environment. Our results demonstrate the effectiveness of Sherlock in localizing to a volume of less than 0.55 cubic meters for 90% of objects.