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Fig. 1. Typical RFID tags used to label objects. The size of the tag depicted in the center is 11 × 5 cm. Abstract— In this paper we analyze whether recent Radio Frequency Identification (RFID) technology can be used to improve the localization of mobile robots and persons in their environment. In particular we study the problem of localizing RFID tags with(More)
Recognizing and recording activities of daily living is a significant problem in elder care. A new paradigm for ADL inferencing leverages radio-frequency-identification technology, data mining, and a probabilistic inference engine to recognize ADLs, based on the objects people use. A key aspect of pervasive computing is using computers and sensor networks(More)
We study activity recognition using 104 hours of annotated data collected from a person living in an instrumented home. The home contained over 900 sensor inputs, including wired reed switches, current and water flow inputs, object and person motion detectors, and RFID tags. Our aim was to compare different sensor modalities on data that approached " real(More)
We propose an approach to activity recognition based on detecting and analyzing the sequence of objects that are being manipulated by the user. In domains such as cooking, where many activities involve similar actions, object-use information can be a valuable cue. In order for this approach to scale to many activities and objects, however, it is necessary(More)
A fundamental difficulty in recognizing human activities is obtaining the labeled data needed to learn models of those activities. Given emerging sensor technology , however, it is possible to view activity data as a stream of natural language terms. Activity models are then mappings from such terms to activity names, and may be extracted from text corpora(More)
We present the design of DyC, a dynamic-compilation system for C based on run-time specialization. Directed by a few declarative user annotations that specify the variables and code on which dynamic compilation should take place, a binding-time analysis computes the set of run-time constants at each program point in the annotated procedure's control-flow(More)
In this paper we present results related to achieving fine-grained activity recognition for context-aware computing applications. We examine the advantages and challenges of reasoning with globally unique object instances detected by an RFID glove. We present a sequence of increasingly powerful probabilistic graphical models for activity recognition. We(More)
Dynamic compilation enables optimization based on the values of invariant data computed at run-time. Using the values of these run-time constants, a dynamic compiler can eliminate their memory loads, perform constant propagation and folding, remove branches they determine, and fully unroll loops they bound. However, the performance benefits of the more(More)
We explore a dense sensing approach that uses RFID sensor network technology to recognize human activities. In our setting, everyday objects are instrumented with UHF RFID tags called WISPs that are equipped with accelerometers. RFID readers detect when the objects are used by examining this sensor data, and daily activities are then inferred from the(More)