Embedded Radio Frequency Identification Research Articles

The impact of run-of-river dams on sediment longitudinal connectivity and downstream channel equilibrium

Considerable research over the past several decades shows that dams, especially large, flow regulating structures, fragment watersheds and serve to disconnect the normative downstream flux of sediment and nutrients. Less attention has addressed smaller, channel-spanning Run-of-River (RoR) dams that are more commonly distributed throughout watersheds. Taking advantage of a suite of RoR dams in New England (USA), we quantify bedload flux into, through, and beyond the reservoir, and we calculate the residence time of gravel clasts.We used traditional channel surveys to evaluate (dis)equilibrium channel form and develop two equilibrium metrics based on bankfull shear stress and the bankfull Shields parameter. Additionally, we compartmentalize the bankfull channel Shields parameter as a linear combination of bedload and suspended load components to better quantify channel evolution in response to changes in sediment supply. To accomplish these goals, we embedded Radio Frequency Identification (RFID) PIT tags in 791 gravel clasts ranging in size from 15 mm to 81 mm, which were subsequently deployed within and upstream of the impounded reservoirs. Among the 503 tracers that were transported from their deployment location, the median cumulative distance traveled was 30 m and the maximum cumulative displacement during the study period was 758 m. Of the total tagged rocks placed at all five sites, 276 rocks were displaced over the dam, 204 of which spent time in the reservoir between high discharge events; the rest were transmitted through the reservoir and over the dam in a single high discharge event. Among those tracers that spent time in the reservoir prior to transmission over the dam, the average reservoir residence times at the different sites ranged from 19 to 203 days. The median grain sizes of tracers that were transported over the dam were identical to those that moved during the study period and similar to the median grain size of the channel bed. The distribution of virtual velocities of those tracers that moved was approximately log-normal and very broadly distributed over more than six orders of magnitude. An analysis of variance revealed that the distribution of velocities was partitioned into two statistically similar groups; with slower velocities in the two smaller watersheds (13 km2–21 km2) with higher average slopes compared to the larger watersheds (89 km2–438 km2) with lower average slopes. We conclude that RoR dams transmit and trap the upstream sediment supply within the same range of physical conditions that produce mobility and trapping in the river's natural reach-scale morphological units. Because RoR dams are likely not trapping more sediment than is typically sequestered in natural river reaches, these dams do not disconnect the normative downstream flux of sediment nor result in channel morphological disequilibrium downstream of the dam. Reaches below RoR dams have similar geomorphic properties to comparable equilibrium reaches unaffected by dams. However, the minimal effect that small, channel spanning RoR dams have on the morphological equilibrium state of a channel does not suggest that RoR dams have no ecological footprint.

Acquiring Bloom Filters Across Commercial RFIDs in Physical Layer

Embedding Radio-Frequency IDentification (RFID) into everyday objects to construct ubiquitous networks has been a long-standing goal. However, a major problem that hinders the attainment of this goal is the current inefficient reading of RFID tags. To address the issue, the research community introduces the technique of Bloom Filter (BF) to RFID systems. This work presents TagMap, a practical solution that acquires BFs across commercial off-the-shelf (COTS) RFID tags in the physical layer , enabling upper applications to boost their performance by orders of magnitude. The key idea is to treat all tags as if they were a single virtual sender, which hashes each tag into different intercepted inventories . Our approach does not require hardware nor firmware changes in commodity RFID tags - allows for rapid, zero-cost deployment in existing RFID tags. We design and implement TagMap reader with commodity device (e.g., USRP N210) platforms. Our comprehensive evaluation reveals that the overhead of TagMap is 66.22% lower than the state-of-the-art solution, with a bit error rate of 0.4%.

Subsea Crude Oil Spill Detection Using Robotic Systems

Underwater Robotic Oil Spill Surveillance (UROSS) system provides constant and autonomous spill surveillance for subsea pipelines. M900 embedded Radio Frequency Identification tags and readers are used to identify pipeline section for surveillance. GY-521 gyrometer and XL-MaxSonar-WR1 ultrasound sensor are used for autonomous navigation. Spills are detected using a METS methane sensor. After spill detection, images of spill site are captured with a L3C-400 Micro Ultras-Miniature Color Camera and spill location is obtained using GPS. Spill Images and location are transmitted to a remote PC on the nearest off shore platform using an Xbee Pro 900HP wireless connection. An Ocean Signal rescueME Personal Beacon Locator transmits a 406 MHz distress signal via satellite to emergency services communicating the identification of a spill. Power analysis showed the system’s ability to remain submerged and to provide surveillance for 100 m sections of a subsea pipeline once every 24 hrs for a month, and can be increased to every hour for 51 months.

Subsea Crude Oil Spill Detection Using Robotic Systems

Underwater Robotic Oil Spill Surveillance (UROSS) system provides constant and autonomous spill surveillance for subsea pipelines. M900 embedded Radio Frequency Identification tags and readers are used to identify pipeline section for surveillance. GY-521 gyrometer and XL-MaxSonar-WR1 ultrasound sensor are used for autonomous navigation. Spills are detected using a METS methane sensor. After spill detection, images of spill site are captured with a L3C-400 Micro Ultras-Miniature Color Camera and spill location is obtained using GPS. Spill Images and location are transmitted to a remote PC on the nearest off shore platform using an Xbee Pro 900HP wireless connection. An Ocean Signal rescueME Personal Beacon Locator transmits a 406 MHz distress signal via satellite to emergency services communicating the identification of a spill. Power analysis showed the system’s ability to remain submerged and to provide surveillance for 100 m sections of a subsea pipeline once every 24 hrs for a month, and can be increased to every hour for 51 months.

Detection From Sub-Sea Crude Oil Pipelines

Crude Oil Spills from subsea pipelines are typically detected after thousands of barrels of oil are spilled into the ocean, affecting marine life, reaching nearby shores and polluting land masses. The Underwater Robotic Oil Spill Surveillance (UROSS) system has been designed to provide constant and autonomous spill surveillance for subsea pipelines. M900 embedded Radio Frequency Identification tags and readers are used to identify pipeline section for surveillance. GY-521 gyrometer and XL-MaxSonar-WR1 ultrasound sensor are used for autonomous navigation beside the crude oil pipeline. Subsea crude oil spills are detected using a METS methane sensor. After spill detection, images of the spill site are captured with a L3C-400 Micro Ultras-Miniature Color Camera and spill location is obtained using Global Positioning System. Spill Images and location are transmitted to a remote PC on the nearest off shore platform using an Xbee Pro 900HP wireless Connection. An Ocean Signal rescueME Personal Beacon Locator also transmits a 406 MHz distress signal via satellite to Emergency Services indicating the identification of a spill. Finite Element Method analysis of the system showed its ability to withstand sea pressures at a depth of 2,250 m. Power analysis showed the system’s ability to remain submerged and to provide surveillance for 100 m section of a subsea pipeline once every 24 hours for over a full month, and this can be increased to once every hour for 51 months with some power modifications.

Intelligent condition perception network towards sustainable manufacturing capability for manufacturing systems

Sustainability has become an important factor from which we can judge the performance of modern manufacturing systems. The condition perception of sustainable manufacturing capability (SMC) can provide reliable manufacturing information and data support for manufacturing systems. This paper proposes an intelligent condition perception network (ICPN) for SMC of manufacturing systems, which focuses on the production condition monitoring, the energy consumption metering, and the perception data transfer. The proposed hybrid wireless perception network consists of the embedded Radio Frequency Identification (RFID) perception modules, embedded energy consumption perception modules and environment perception modules. In view of the several heterogeneous networks might coexist in the manufacturing environment, the heterogeneous networks adaptation device is designed to figure out the problem of differences of data transmission in heterogeneous networks. Finally, a prototype system is deployed in a laboratory environment. The experimental results demonstrate that the system can satisfy the requirements of condition perception for SMC.

Banknote Validation through an Embedded RFID Chip and an NFC-Enabled Smartphone

With the new, state-of-the-art printing devices and equipment, there has been rapid growth in the counterfeiting of banknotes. Traditional security features on banknotes are easy targets for counterfeiters, and they can easily imitate the original banknotes with fake ones. Conventional methods for validating currency require specialized devices for the authentication of banknotes. However, cost and lack of mobility of sophisticated banknote validation devices are big problems for general consumers. Modern digital solutions are attempting to complement the traditional security features through embedding radio frequency identification (RFID) chips in the banknotes, for example, Euro currency. Unfortunately, the requirement of specialized RFID readers for banknote validation impedes their widespread proliferation among consumers. To overcome this problem, a new method of banknote validation using an RFID chip and an NFC-enabled smartphone is presented. The consumer sends a banknote validation request to the Monetary Agency (MA) using her or his smartphone and an Internet connection. TheMAreplies by sending a random challenge to the consumer’s smartphone. The RFID chip in the banknote receives the challenge, via the NFC, and calculates an equivalent response to theMA’s challenge. If any of the messages are incorrect, authentication is denied. By the proposed method, consumers can easily and instantly check the originality of currency notes with theMAusing their smartphones and an Internet connection. The proposed system is less expensive, computationally, than regular methods and preserves the privacy of people who carry banknotes.