Proximity interactions between wireless sensors and their application

Abstract

Many applications in ubiquitous computing rely on knowing where people and objects are relative to each other. By placing small wireless sensors on people, at specific locations, and on or in a wide variety of everyday objects we can collect these proximate relationships and deduce much about a person's or an object's context. This paper investigates the practical issues of recording these proximity interactions using RF wireless sensors and explores the benefits of collecting/mining proximity data and how user context and usage habits can be inferred for use by proactive applications. We describe some of the issues we faced in collecting usable proximity data from RF wireless sensors. Specifically, we discuss some of the ranging experiments we conducted, our approach to utilizing the limited local data store, and how we implemented a low-overhead time synchronization scheme. We present initial results from one of the applications we are targeting: a proactive reminding system that informs users when they leave important items behind.

Unsupervised Grouping of Moving Objects Based on Agglomerative Hierarchical Clustering

“…If there are more than two people wearing tag readers in close vicinity, it is difficult to identify who is the true carrier since all the readers might detect the same tags. Similar to this approach, radio signal strength can measure the proximity of two devices [5]. The signal strength is easily affected by the orientation of the body and the placement of devices.…”

“…These examples are realized by observing the coexistence of objects. For example, a radio frequency identification (RFID) receiver worn by a person or embedded into a bag can be used to detect RFID-tagged objects [5,19]. However, the similarity of the movement pattern would provide more reliable information than mere coexistence.…”

A study on automatic recognition of object use exploiting motion correlation of wireless sensors

“…A common solution is to detect whether a particular user, or rather his arm, is in close proximity to an object by employing the RFID [4,8,31] technology or other RFbased solutions [6]. Each object is equipped with an RFID tag, while the user wears a reader on his hand or lower arm.…”

Speech as a feedback modality for smart objects

“…In immediate proximity, the recognised context delivered by a smart object is considered relevant and will be played by the doll. The challenges in collecting proximity data for interacting wireless sensor nodes are described by experiments by [15]. In our approach we profit from the steep increase in RSSI in close proximity, which makes the evaluation more reliable.…”