A low cost solution for RFID sensing

Abstract

Recent years have witnessed a surge of wireless and mobile devices and their sensing technologies. Among these wireless technologies, RFID (Radio Frequency IDentificaion) sensing has attracted wide attention in both academia and industry due to its innovative applications including logistics, localization and tracking, health care, human-computer interaction, etc. The RFID sensing technologies can be roughly divided into two categories: (1) Contact-based sensing and (2) Contact-free sensing. In contact-based sensing, by attaching lightweight RFID tags on target objects, the movement of objects can be tracked by the movement of the tags. In contact-free scenarios, the tags do not physically contact to the objects. Through the analysis of backscatter signals of deployed RFID tags, the movement of objects can still be inferred since the movement of objects results in the change of backscatter signals (i.e., RSSI, phase, etc.). This thesis studies RFID sensing technology with physical layer information and explores the possibility of implementing novel applications using COTS (commercial off-the-shelf) RFID systems in both contact and contact-free manners. While the cost of an individual RFID tag can be kept very low, COTS RFID readers still incur very high cost due to non-trivial RF implementations. Therefore, we develop an innovative low-cost RFID solution to reduce the cost of RFID sensing technology for general purpose. The main contents of this thesis are follows. First, we study the problem of using the commodity RFID system to monitor human respiration in contact-based manner. Respiration monitoring helps to assess general personal health and gives clues to chronic diseases. Yet current respiration monitoring technologies are inconvenient and intrusive. For instance, typical respiration monitoring devices need to attach nasal probes or chest bands to users. Wireless sensing technologies have been applied to monitor respiration using radio waves without physical contact. Those wireless sensing technologies, however, require customized radios which are not readily available. More importantly, due to interference, such technologies do not work well with multiple users. With multiple users in presence, the detection accuracy of existing systems decreases dramatically. We propose to monitor users' respiration using commercial-off-the-shelf (COTS) RFID systems. In our system, passive lightweight RFID tags are attached to users' clothes and backscatter radio waves, and commodity RFID readers report low-level data (e.g., phase values). We reliably detect the effective human respiration corresponded signal and track periodic body movement due to inhaling and exhaling by analyzing the low-level data reported by commodity readers. To enhance the measurement robustness, we synthesize data streams from an array of multiple tags to improve the monitoring accuracy. Our design follows the standard EPC protocol which arbitrates collisions in the presence of multiple tags. We implement a prototype of the respiration monitoring system with commodity RFID systems. The experiment results show that the prototype system can simultaneously monitor respiration with high accuracy even with the presence of multiple users. Second, we study the problem of human activity recognition using commodity RFID system in contact-free manner. Wireless sensing techniques for tracking human activities have been vigorously developed in recent years. Yet current RFID based human activity recognition techniques need either direct contact to human body (e.g., attaching RFIDs to users) or specialized hardware (e.g., software defined radios, antenna arrays). How to wirelessly track human activities using commodity RFID systems without attaching tags to users (i.e., a contact-free scenario) still faces lots of technical challenges. In this thesis, we quantify the correlation between RF phase values and human activities by modeling intrinsic characteristics of signal reflection in contact-free scenarios. Based on the signal reflection model, we introduce TACT that can recognize human activities using commodity RFIDs without attaching any RFID tags to users. TACT first reliably detects the presence of human activities and segments phase values. Then, candidate phase segments are classified according to their coarse-grained features (e.g., moving speed, moving distance, activity duration) as well as their fine-grained feature of phase waveform. We deploy and leverage multiple tags to increase the coverage and enhance the robustness of the system. We implement TACT with commodity RFID systems. We invite 12 participants to evaluate our system in various scenarios. The experiment results show that TACT can recognize eight types of human activities with 93.5% precision under different and challenging experiment settings. Third, to further reduce the system cost, we present our experience in design, implementation, evaluation and application of a low-cost RFID solution for general and novel RFID applications. Different from high-end commodity RFID readers which implement the full protocol stack of RFID standard, the proposed low-cost RFID solution implements essential functionalities with low-cost radio components (a total cost of <30 USD v.s. >2000 USD of commercial RFID readers) and supports practical applications including general RFID query as well as RFID based sensing applications. The proposed solution is built in a distributed way where the functionalities of interrogating RFID tags and receiving their backscattered signals are separated into two modules. A set of innovative techniques are devised, e.g., packet-in-packet communication, carrier frequency offset cancellation, etc. to address a range of design challenges including cross-technology communication, correction of carrier frequency offset, etc. Three case studies on applying the proposed solution in building useful applications are presented at the end of this work.