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—Indoor localization is of great importance for a range of pervasive applications, attracting many research efforts in the past two decades. Most radio-based solutions require a process of site survey, in which radio signatures are collected and stored for further comparison and matching. Site survey involves intensive costs on manpower and time. In this(More)
We conducted a case-control study using 190 Han children with and without autism to investigate prenatal and perinatal risk factors for autism in China. Cases were recruited through public special education schools and controls from regular public schools in the same region (Tianjin), with frequency matching on sex and birth year. Unadjusted analyses(More)
Physical-layer identification utilizes unique features of wireless devices as their fingerprints, providing authenticity and security guarantee. Prior physical-layer identification techniques on radio frequency identification (RFID) tags require nongeneric equipments and are not fully compatible with existing standards. In this paper, we propose a novel(More)
Different from online shopping, in-store shopping has few ways to collect the customer behaviors before purchase. In this paper, we present the design and implementation of an on-site Customer Behavior IDentification system based on passive RFID tags, named CBID. By collecting and analyzing wireless signal features, CBID can detect and track tag movements(More)
—Crowd counting, which count or accurately estimate the number of human beings within a region, is critical in many applications, such as guided tour and crowd control. A crowd counting solution should be scalable and be minimally intrusive (i.e., device-free) to users. Image-based solutions are device-free, but cannot work well in a dim or dark(More)
Localization is a fundamental issue of wireless sensor networks that has been extensively studied in the literature. The real-world experience from GreenOrbs, a sensor network system in the forest, shows that localization in the wild remains very challenging due to various interfering factors. In this paper we propose CDL, a Combined and Differentiated(More)
Localization is a fundamental issue of wireless sensor networks that has been extensively studied in the literature. Our real-world experience from GreenOrbs, a sensor network system deployed in a forest, shows that localization in the wild remains very challenging due to various interfering factors. In this paper, we propose CDL, a Combined and(More)
Device-free object tracking provides a promising solution for many localization and tracking systems to monitor non-cooperative objects, such as intruders, which do not carry any transceiver. However, existing device-free solutions mainly use special sensors or active RFID tags, which are much more expensive compared to passive tags. In this paper, we(More)