Tag Tracking Research Articles

A Review of Five Existing Hornet-Tracking Methods.

Hornet is a general term for insects of the genus Vespa (Hymenoptera: Vespidae). Hornets are predatory insects distributed worldwide. They often appear at apiaries in groups to prey on honey bees, and cause incalculable losses in the honey bee industry. In the face of hornet intrusion, tracking a homing hornet to find its nest is the most efficient way to discover and eliminate the hornets around an apiary. Here, five hornet-tracking methods (hornet tag tracking, triangulation, thermal imaging technology, harmonic radar, and radio telemetry) are reviewed. The advantages, disadvantages and feasibility of each method are discussed to improve the strategies for tracking hornets. Therefore, this review provides ideas for the development of hornet-tracking technology and for improving honey bee protection.

Salmon shark seasonal site fidelity demonstrates the influence of scale on identifying potential high-use areas and vulnerabilities

Considering habitat use throughout the whole range of a highly mobile marine species is necessary to understand life history, identify vulnerabilities, and inform effective management. We used satellite tagging data from 128 adult female salmon sharks Lamna ditropis to identify seasonal hotspots of activity in an extended California Current region (ECCR; encompassing the California Current Large Marine Ecosystem), an area far away from their well-described primary habitat in the Alaska Downwelling Region where they have been documented, but whose utility has been poorly understood. Tag track durations had a mean of 447.7 ± 381 d, and 88 sharks (68.8%) visited the ECCR, comprising 33.6% of 28019 total daily Argos detections. Tracking data revealed that the timing and duration of migrations to the ECCR varied, but salmon shark distribution within the ECCR displayed consistent latitudinal shifts in accordance with regional oceanographic seasons. High site fidelity across multi-year tracks to high-productivity features, such as sea banks, and previously published knowledge of salmon shark life history suggest that the ECCR provides important foraging habitat which may be linked to reproductive success. The data reveal high overlap of salmon shark distribution with cumulative fishing effort collected by Global Fishing Watch for 2012-2019, particularly around seasonal hotspots, suggesting that female salmon sharks might be at risk of fisheries encounters. Collectively, our findings emphasize the importance of the ECCR in salmon shark life history and demonstrate the influence of spatial and temporal scale on interpretation of large movement data sets and identification of critical habitat outside of well-studied regions.

Lagrangian tracking of long-lasting plastic tags: From lobster fisheries in the USA and Canada to Macaronesia

Plastic waste from the fishing industry, particularly lobster trap identification tags from the USA and Canada, poses a significant threat to marine ecosystems due to its resilience. This study unveils a novel link between North American fisheries and the appearance of these plastic tags in Macaronesia. Collected in the Azores and Canary Islands, these tags offer a unique insight into the sources and spatio-temporal scales of marine plastic pollution. Ocean model data indicates the Labrador Current and Gulf Stream as key forces transporting these tags. Virtual particle simulations show a small fraction reaching Macaronesia (4.12 % in the Azores, 0.76 % in the Canary Islands), suggesting real ocean drift. The Azores, with more collected tags, are more susceptible, and tags can reach Macaronesia in under a year. These findings underscore the urgency of better waste management and emphasize the role of citizen science in monitoring and combating marine pollution.

A case report assessing the utility of a low-cost tracking GPS device for monitoring terrestrial mammal movements

BackgroundAccurate data on animal movements can highlight behavioural and ecological issues, such as territorial interactions, barriers to migration patterns, including compromised movement corridors, or avoidance of deteriorating habitats, and disease transmission, thus helping in conservation decision making. This study examines the utility of mOOvement global positioning system (GPS) tags, a low-cost cattle ear tag tracking device to monitor movements of terrestrial mammal populations in South Australia.ResultsStationary tags (n = 40) were used to test horizontal accuracy with a median location error of 33.26 m (IQR = 16.9–59.4), and maximum recorded error of 410 m. The locational accuracy was weakly influenced by the horizontal dilution of precision (HDOP), a measure of satellite availability and geometry, and overhead canopy cover. Numerous tags produced infrequent and inconsistent readings, median of 12 records per day (IQR = 6–12), correlating negatively with the tag’s distance from the centrally located LoRa antenna; however, some tags recorded fewer than one position per day.ConclusionsWe propose that the primary cause of mOOvement tag inadequacy is the use of only the GPS satellite constellation (USA, 1978), which does not provide adequate coverage in either satellite number or geometry in the sky at the − 35° latitude to calculate accurate positions regularly over 24 h, unlike the multiple constellations available in the global navigation satellite system (GNSS). We conclude that GPS tags are unsuitable for studies requiring high locational accuracy or identification of an individual’s social interactions, where the GPS constellation has a limited number of satellites available during prolonged periods. They can, however, be used to provide estimates of home range size or track large scale daily movements of animals in more equatorially located regions.

Simple Yet Secure Encoder Architecture and Ultralightweight Mutual Authentication Protocol for RFID Tags in IoT

Internet of things (IoT) has evolved as the internet of everything, and it has grabbed the interest of all the researchers in recent days. Almost all the objects, including nonelectronics devices, can also be connected with the internet through radio frequency identification (RFID) technology. The security of the perception layer is crucial to secure the entire IoT network. RFID-enabled IoT perception layer has secured reader-to-server channel and unsecured tag to reader channel. Hence, securing the unsecured communication channel between the reader and the tag is the need of the hour. This work proposes a simple yet secure permutation approximate adder (SYSPXA)-based RFID mutual authentication protocol to address the need. The proposed protocol dramatically reduces the tag’s storage and computational overhead. It needs 40% less storage and 66.7% less permutation operation in comparison with the existing protocols. Nondisclosure of the key and freshness of key, IDS and random numbers at every mutual authentication process gives resistance to the protocol against de-synchronization attack, disclosure attack, tag tracking, replay attack. The SYSPXA protocol is validated for its security features using Burrows–Abadi–Needham (BAN) logic formal verification. The performance and security of the proposed protocol are contrasted with various futuristic permutation-based protocols, and its superiority over other protocols is highlighted. We have simulated the SYSPXA protocol with ModelSim tool for verifying its functionality. The protocol encoder architecture is implemented in the Intel cyclone IV Field Programmable Gate Array (FPGA) EP4CE115F29C7 device.

A lightweight secure authentication approach based on stream ciphering for RFID-based Internet of Things

In this paper, a new lightweight RFID-based authentication approach is proposed that uses stream ciphering techniques to preserve privacy between legitimate components. The proposed approach uses various key-stream generators such as And2LFSR, Geffe, and majority-based to eliminate the inherent linearity of LFSRs and construct a non-linear Pseudo-Random Number Generators (PRNG). The informal security analysis indicates that the proposed approach provides forward security and resists eavesdropping, tag tracking, replay, cloning, and DoS attacks. Moreover, simulations conducted through Cooja tool illustrate the effect of generator polynomial degree and proposed combinational generators on BER. The BER of communications has been evaluated in different quantities of (Eb/N0), ranged between 1 and 10, using the proposed generators along with different error control techniques. In addition, evaluations indicate that the proposed approach outperforms in terms of computational cost, storage spaces, and communication cost. Furthermore, statistical analysis proves resistance of the proposed approach to guessing attacks.

Foraging habitat characterization of green sea turtles, Chelonia mydas, in the Cenderawasih Bay, Papua, Indonesia: Insights from satellite tag tracking and seagrass survey

Abstract. Tapilatu RF, Wona H, Mofu B, Kolibingso D, Alzair N, Erdmann M, Marunaya B. 2022. Foraging habitat characterization of green sea turtles, Chelonia mydas, in the Cenderawasih Bay, Papua, Indonesia: Insights from satellite tag tracking and seagrass survey. Biodiversitas 23: 2783-2789. The distribution area of green turtles is not yet known in Cenderawasih Bay. On 20 November 2020, two satellite transmitters were attached to two female green turtles (Chelonia mydas Linnaeus, 1758) on Kalilemon, Southwest Cenderawasih Bay, Papua Province, Indonesia. Kalilemon area and Mangga Island as part of Kwatisore waters are the major foraging areas for this species and are under threat of turtle opportunistic poachers. The results show that the two turtles (Mary and Nona) dispersed and used limited but consistent and different foraging grounds during the tracking period through the satellite tags between November 2020-April 2021 at Mangga Island and Kalilemon. The composition of seagrass at both stations consisted of the same five species belonging to the families Cymodoceae and Hydrocharitaceae, with relatively different qualitative abundances. Overall, the mean chlorophyll-a content during the study period from November 2020-April 2021 ranged from 0.25-0.55mg/m3 at both foraging grounds (Mangga Island and Kalilemon). The mean SST during the study period ranged from 30.61-31.77oC in both locations. Before the next tracking attempt, more data on seasonal foraging and nesting activities are required. The result of this research is vital to determine the foraging grounds for green turtles related to the seagrass species with its abundance and key environmental factors in the management and conservation of sea turtles in the Cenderawasih Bay area.

Novel lightweight RFID authentication protocols for inexpensive tags

Radio-frequency identification (RFID) systems represent a support technology employed for the internet of things (IoT). Since RFID systems are now used extensively, it would be a mistake to disregard security problems and user privacy protection. However, constraints on computing power and storage resources in inexpensive tags of RFID have made the execution of security issues difficult. In other words, a persistent formidable challenge to RFID security is to design ultra-lightweight authentication protocols for RFID systems in acceptable compatibility with EPC Class-1 Generation-2 standards. Xiao et al. has recently proposed an appropriate lightweight authentication protocol for inexpensive tags by benefiting from the lightweight block cipher algorithm. They have claimed that their proposed protocol is resistant to all of the known attacks which may occur in RFID systems. In this paper, we show that the LRSAS protocol is vulnerable to replay, reader impersonation, tag tracking, and desynchronization attacks. We demonstrate that the use of fixed messages in the communication between the tag and the reader is led to these attacks. To improve the LRSAS protocol, We propose three lightweight protocols LRSAS+, LRARP, and LRARP+. We analyze the security level of the proposed protocols and prove the security of the proposed design using Gong–Needham–Yahalom logic (GNY logic). We also formally confirmed the security of the proposal using the Scyther simulation tool. According to security analysis, we can observe that these protocols have a high level of security. Furthermore, the performance of the proposed protocols is analyzed. A comparison of the performance of these three protocols with similar protocols shows that these protocols are at a better level than similar protocols in terms of computational costs, storage costs, and communication costs.

Long-term tracking and quantification of individual behavior in bumble bee colonies

Social insects are ecologically dominant and provide vital ecosystem services. It is critical to understand collective responses of social insects such as bees to ecological perturbations. However, studying behavior of individual insects across entire colonies and across timescales relevant for colony performance (i.e., days or weeks) remains a central challenge. Here, we describe an approach for long-term monitoring of individuals within multiple bumble bee (Bombus spp.) colonies that combines the complementary strengths of multiple existing methods. Specifically, we combine (a) automated monitoring, (b) fiducial tag tracking, and (c) pose estimation to quantify behavior across multiple colonies over a 48 h period. Finally, we demonstrate the benefits of this approach by quantifying an important but subtle behavior (antennal activity) in bumble bee colonies, and how this behavior is impacted by a common environmental stressor (a neonicotinoid pesticide).

Using synthetic data generation to train a cardiac motion tag tracking neural network.

A CNN based method for cardiac MRI tag tracking was developed and validated. A synthetic data simulator was created to generate large amounts of training data using natural images, a Bloch equation simulation, a broad range of tissue properties, and programmed ground-truth motion. The method was validated using both an analytical deforming cardiac phantom and in vivo data with manually tracked reference motion paths. In the analytical phantom, error was investigated relative to SNR, and accurate results were seen for SNR>10 (displacement error <0.3mm). Excellent agreement was seen in vivo for tag locations (mean displacement difference = -0.02pixels, 95% CI [-0.73, 0.69]) and calculated cardiac circumferential strain (mean difference = 0.006, 95% CI [-0.012, 0.024]). Automated tag tracking with a CNN trained on synthetic data is both accurate and precise.

Experimental determination of residence time for sockeye salmon spawners on spawning grounds in the littoral zone of Lake Nachikinskoye (Kamchatka)

Residence time of late-race sockeye spawners on spawning grounds located in the littoral zone of Lake Nachikinskoye in southern Kamchatka is determined directly using 11 series of tagging and tracking of tags conducted in 2018 and 2020 (700 tagged individuals). The residence time is the key parameter for calculation of the spawners number on the data of repeated observations from the beginning to the end of spawning. Methodology of the experiment is described in details and all data of measurements are presented. Impact of certain variables on the target function is discussed. The residence time is estimated as 5 days.

TagFi

Tag localization is crucial for many context-aware and automation applications in smart homes, retail stores, or warehouses. While custom localization technologies (e.g RFID) have the potential to support low-cost battery-free tag tracking, the cost and complexity of commissioning a space with beacons or readers has stifled adoption. In this paper, we explore how WiFi backscatter localization can be realized using the existing WiFi infrastructure already deployed for data applications. We present a new approach that leverages existing WiFi infrastructure to enable extremely low-power and accurate tag localization relative to a single scanning device. First, we adopt an ultra-low power tag design in which the tag blindly modulates ongoing WiFi packets using On-Off Keying (OOK). Then, we utilize the underlying physical properties of multipath propagation to detect the passive wireless reflection from the tag in the presence of rich multipath propagations. Finally, we localize the tag from a single receiver by forming a triangle between the tag reflection and the LoS path between the two WiFi transceivers. We implement TagFi using a customized backscatter tag and off-the-shelf WiFi chipsets. Our empirical results in a cluttered office building demonstrate that TagFi achieves a median localization accuracy of 0.2m up to 8 meters range.

Software-Defined RFID Readers: Wireless Reader Testbeds Exploiting Software-Defined Radios for Enhancements in UHF RFID Systems

In recent years, RF identification (RFID) technology in the ultrahigh-frequency (UHF) range has become increasingly important in many applications, especially in the context of both the Internet of Things (IoT) and Industry 4.0. RFID is no longer simply a matter of identification; today, it is mainly concerned with recording data from the surrounding environment. As a result, researchers are working on the integration of sensors (or even small actuators) in passive RFID transponders (tags) for a variety of different applications and also on the localization and tracking of RFID tags attached to various objects and machinery. Another key aspect in UHF RFID technologies is security, as the data transmitted may be confidential and should not be shared with third parties. For the fast verification of novel algorithms in localization and novel protocols for security, wireless testbeds allow swift verification of these designs under real-world or real-time conditions [1]. Wireless testbeds are widely used in research and require scalability, modularity, and extendibility of the hardware and software. These needs can be achieved by using software-defined radios (SDRs). In the case of UHF RFID, SDR-based RFID readers have been developed and used as wireless testbeds for enhancements in UHF RFID systems.

Arbitrary Point Tracking with Machine Learning to Measure Cardiac Strains in Tagged MRI.

Cardiac tagged MR images allow for deformation fields to be measured in the heart by tracking the motion of tag lines throughout the cardiac cycle. Machine learning (ML) algorithms enable accurate and robust tracking of tag lines. Herein, the use of a massive synthetic physics-driven training dataset with known ground truth was used to train an ML network to enable tracking any number of points at arbitrary positions rather than anchored to the tag lines themselves. The tag tracking and strain calculation methods were investigated in a computational deforming cardiac phantom with known (ground truth) strain values. This enabled both tag tracking and strain accuracy to be characterized for a range of image acquisition and tag tracking parameters. The methods were also tested on in vivo volunteer data. Median tracking error was <0.26mm in the computational phantom, and strain measurements were improved in vivo when using the arbitrary point tracking for a standard clinical protocol.

Characterization of acoustic detection efficiency using a gliding robotic fish as a mobile receiver platform

BackgroundAutonomous underwater vehicles (AUVs) and animal telemetry have become important tools for understanding the relationships between aquatic organisms and their environment, but more information is needed to guide the development and use of AUVs as effective animal tracking platforms. A forward-facing acoustic telemetry receiver (VR2Tx 69 kHz; VEMCO, Bedford, Nova Scotia) attached to a novel AUV (gliding robotic fish) was tested in a freshwater lake to (1) compare its detection efficiency (i.e., the probability of detecting an acoustic signal emitted by a tag) of acoustic tags (VEMCO model V8-4H 69 kHz) to stationary receivers and (2) determine if detection efficiency was related to distance between tag and receiver, direction of movement (toward or away from transmitter), depth, or pitch.ResultsDetection efficiency for mobile (robot-mounted) and stationary receivers were similar at ranges less than 300 m, on average across all tests, but detection efficiency for the mobile receiver decreased faster than for stationary receivers at distances greater than 300 m. Detection efficiency was higher when the robot was moving toward the transmitter than when moving away from the transmitter. Detection efficiency decreased with depth (surface to 4 m) when the robot was moving away from the transmitter, but depth had no significant effect on detection efficiency when the robot was moving toward the transmitter. Detection efficiency was higher when the robot was descending (pitched downward) than ascending (pitched upward) when moving toward the transmitter, but pitch had no significant effect when moving away from the transmitter.ConclusionResults suggested that much of the observed variation in detection efficiency is related to shielding of the acoustic signal by the robot body depending on the positions and orientation of the hydrophone relative to the transmitter. Results are expected to inform hardware, software, and operational changes to gliding robotic fish that will improve detection efficiency. Regardless, data on the size and shape of detection efficiency curves for gliding robotic fish will be useful for planning future missions and should be relevant to other AUVs for telemetry. With refinements, gliding robotic fish could be a useful platform for active tracking of acoustic tags in certain environments.

Locating Targets in RFID System in a Sensing Covered Anchor-Free Network

In an RFID system, the RFID readers consume huge energy and are considerably expensive in practical applications. To minimize the total number of readers with guaranteed surveillance such that the position of each tag can be uniquely determined is a challenge. This paper considers a simple but practically useful model of anchor-free network of RFID readers where each tag falls within the sensing zone of at least two readers. To maintain the quality of service in the real applications, a practical condition, the communication range is at least twice its sensing range, is considered. Under this condition, a characterization of a network is proved. An efficient algorithm for recognizing such a network is then developed without any initial position information of the readers. Using these readers as the references, an algorithm is designed for finding the exact positions of the tags in distributed manner. Unlike the existing techniques, it requires no external references for tag tracking. The proposed technique finds at most two possible positions (in some cases, unique position), out of which one is correct, for each tag.

Nesting ecology of flatback sea turtles Natator depressus from Delambre Island, Western Australia

Nest site selection is likely to be important for the fitness of sea turtle populations, but data on the environmental drivers of nest site selection and other important parameters like nest site fidelity and inter-nesting and remigration intervals are limited. We address these questions using data on flipper tag resightings and track counts from flatback turtles (Natator depressus) from Delambre Island in Western Australia collected over 2–3 weeks each nesting season across six nesting seasons. The median inter-nesting interval was 13 days (range 9–17 days) and the mean±s.d. remigration interval was 1.99±0.95 years. Turtles had around 10% probability of returning to the same sector of the beach (150-m-long sections). The median distance between subsequent emergences (whether false crawls were included or not) was ~450m. The number of turtles both emerging and successfully nesting was higher when air temperature and humidity were lowest and emergences increased slightly with tide height. Sector of the beach was by far the strongest predictor of nest site, with turtles showing preference for the less exposed side of the island. The results of this study will assist with future monitoring of this population and the management of threats related to coastal development and activities.

Precise capture of fish movement trajectories in complex environments via ultrasonic signal tag tracking

Ultrasonic tag tracking technology has been widely used in fish behavior research, but most existing studies obtain fish movement trajectories through use of supporting software or post-processing services provided by the manufacturers of the relevant equipment. Articles concerning fish positioning principles and optimization and processing methods suited to complex water environments, are rarely published. This paper proposes a set of solutions permitting precise capture of fish movement trajectories. The proposed methods can effectively mitigate the impact of difficult conditions such as partial loss of time synchronization signals and data containing gross error-bearing observations on the process of locating tagged fish. Test results show that: (1) Even if time synchronization signals for a continuous 2 h period are lost, the accuracy of time synchronization between the hydrophones remains consistent with the requirements of meter-level positioning. (2) The proposed method can effectively detect the existence of gross errors exceeding 10 m in the observation data; the success rate of the method in identifying unique gross error-bearing observations was 99.7%. (3) Based on existing hydrophones with millisecond-level observation precision, three-dimensional (3D) positioning of fish-borne signal tags to 2˜5 m precision is possible.

Passive radio-frequency identification ranging, a dense and weather-robust technique for landslide displacement monitoring

Ground deformation monitoring at a local scale requires accuracy, along with dense spatio-temporal resolution. Radio-Frequency Identification (RFID) technology is proposed as an alternative to classical geodetic methods for monitoring displacements of a landslide. Passive RFID tags allow for a very dense resolution, both in time and space, at the scale of a 100-m-long surface. By deploying 19 passive RFID tags on a landslide for 5 months, this study validates the technique by comparison with laser total station and wire extensometer data. The accuracy of the RFID technique was 1 cm during normal weather and up to 8 cm during snow events. The results demonstrate that RFID tag tracking can monitor landslide displacements with multiple sensors at low cost, providing dense spatio-temporal data. This technique could potentially be used for other applications such as monitoring volcanic activity, buildings, unstable rocks or snow cover.

A new lightweight authentication protocol in IoT environment for RFID tags

Nowadays, internet of things (IoT) is a prominent technology that provides the field for connection and information transfer through communicational networks like internet and intranet. Since IoT is applied in various functions so that personal information of individuals or objects may be read without consent of them or in absence of a secure protocol, that is a challenge in this part, this study aimed at identifying tags efficiently in order to protect privacy of things against attackers. In this research, a two-factor authentication protocol based on the public key cryptography has been presented in order to protect privacy. It has been tried in this protocol to diminish complicated calculations while the proposed method can resist against some attacks like tampering with tag and tag reader, tag tracking, man-in-the-middle attack, and replay attack. To examine the proposed method, application of paying toll in traffic management was used. Various traffic models have been considered to pay toll in proposed model and implementation of this method was done in simulation environment of MATLAB. In this simulation, two cryptography algorithms with Robin and ECC public keys with keys in different sizes were evaluated and results showed that almost all of passed tags were identified using an anticipation rate with high rate between tag and tag reader in a system implemented with Rabin algorithm. Moreover, this ratio was higher than 90% in a system that was implemented with ECC algorithm. However, application of conventional symmetric cryptographic algorithms such as AES can reduce ratio of read tags to lower than 20%.