Добірка наукової літератури з теми "Radio-tagged animals"

Platypuses, Ornithorhynchus anatinus, have been studied on the Duckmaloi River, New South Wales, in a long term mark-release-recapture project from 1986 to 1996. Some animals are recaptured regularly, while others are trapped only once. A high percentage of juveniles are never retrapped. New animals continue to be captured each year. Hence radio-tracking was employed to examine the movements of animals within the river system including their spatial utilisation of the Duckmaloi Weir. Concurrent studies on activity patterns and burrow usage were undertaken. Seventeen animals (I 0 juveniles, 2 subadults and 5 adults) were radio-tracked for various lengths of time between January and October 1993. Telemetric data revealed that radio-tagged animals were not recaptured on all possible occasions. Home ranges (length of river) varied from 0.5 km to 3.5 km. Home ranges of all animals, overlapped extensively, while core area overlap also occurred in the pool behind the Duckmaloi weir. One juvenile male dispersed 8.5 km upstream from the weir. Platypuses typically utilised areas when feeding with water depth between I to 2.5 m, rarely using areas less than 0.5 m deep. Juvenile platypuses were crepuscular and nocturnal, while adults, although mainly nocturnal also exhibited individual variations in diurnality. Although some individuals remained active throughout the night, others returned to burrows before re-entering the water. Animals commonly returned to certain burrow complexes with some exhibiting a higher degree of burrow site specificity than others. Certain burrows were used by nearly all radio-tagged animals over time while others were used by only a select number of individuals. Some animals tracked in the weir pool were found to share burrows.

I describe a technique to differentiate between activities of radio-tagged animals solely from radio signals. Signal amplitude and pulse interval data are transformed with time series analysis, and variables measured from the transformation are classified with discriminant function analysis. An example is given with known reference radio signals for three behaviors from striped skunks (Mephitis mephitis) in which 75% of the reference signals are classified correctly. If the classification is adjusted to allow for unclassifiable signals, then 23% are unclassifiable, but of the remaining 77%, 84% are classified correctly.

Radio-tracking tagged wildlife remains a critical research technique for understanding the movements, behaviours and survival of many species. However, traditional hand-held tracking techniques on the ground are labour intensive and time consuming. Therefore, researchers are increasingly seeking new technologies to address these challenges, including drone radio-tracking receivers. Following the implementation of drone radio-tracking techniques for five different threatened species projects within different habitat and landscape types, we identified the need to quantify the relative spatial extent of surveys using both drone and hand-held techniques for each project. This was undertaken using viewshed analyses. These analyses demonstrated that survey coverage with drone-based radio-tracking was substantially greater than that of hand-held radio-tracking for all species and landscapes examined. Within mountainous landscapes, drone radio-tracking covered up to four times the area of hand-held tracking, whereas in flat to undulating landscapes, drone surveys covered up to 11.3 times the area that could be surveyed using hand-held techniques from the same locations on the ground. The viewshed analyses were also found to be a valuable visualisation tool for identifying areas for targeted surveys to reduce the risk of ‘losing’ tagged animals, which has traditionally been one of the biggest radio-tracking challenges.

In animal tracking applications, smaller transmitters can reduce the impact of the transmitter on the tagged animal and thus provide more accurate data about animal behavior. By combining a novel circuit design and a newly developed micro-battery, we developed frequency-programmable and more powerful radio frequency transmitters that are about 40% smaller and lighter in weight than the smallest commercial counterpart for animal monitoring at the time of development. The new radio frequency transmitter has a miniaturized form factor for studying small animals. Designs of two coding schemes were developed: one transmits unmodulated signals (weight: 152 mg; dimensions: Ø 2.95 mm × 11.22 mm), and the other transmits modulated signals (weight: 160 mg; dimensions: Ø 2.95 mm × 11.85 mm). To accommodate different transmitter life requirements, each design can be configured to transmit in high or low signal strength. Prototypes of these transmitters were evaluated in the laboratory and exhibited comparable or longer service life and higher signal strength compared to their smallest commercial counterparts.

Recent technological advances have multiplied the variety of biologgers used in wildlife research, particularly with small-bodied animals. Passive integrated transponders (PIT) have been used for decades to log visits of tagged animals at reader-equipped artificial feeders or roost boxes. More recently, novel miniaturized sensor nodes can collect data on social encounters among tagged individuals in any location. Combining these systems allows researchers to gather high-resolution tracking data on certain individuals from their long-term PIT-tagged animal populations. However, there can be a risk of interference among tracking systems. Here we tested whether placing an additional biologging sensor on top of a PIT tag might attenuate the magnetic field reaching the PIT tag and, in turn, hamper reading success of the radio-frequency identification (RFID) reader. We also evaluated data transmission by a digital sensor node in the presence of a magnetic field created by the RFID antenna. The combination of this RFID system and wireless biologging sensors works without error, suggesting that the simultaneous use of PIT tags and other digital biologgers, e.g., miniaturized GPS-loggers, should also work together properly when communication channels do not overlap. The combination of long-term monitoring with PIT tags and short-term tracking with biologging sensor nodes creates exciting new opportunities to gather rich social data when individuals are not present at RFID reader stations.

In winter, 1981, 103 reindeer, out of a population of 3600, were herded into a fence by snowmobiles and marked. During the next 4 1/2 years reindeer were followed from the ground, or by radiolocations from an airplane. On the average one animal was tagged per 42 animals in any group. A total sample of 175 locations in all seasons indicated that snow conditions, traffic on a road lying parallel to a railroad, and the damming of a lake significantly affected annual distribution as compared with expected modern as well as prehistoric distribution.

Long-distance movements of juvenile male and female brushtail possums (Trichosurus vulpecula) at a farmland site, Hawke's Bay, New Zealand, were studied by radio-tracking. About 20% of radio-tagged possums dispersed more than 2 km, moving up to 11.5 km from their natal area, most in a north-easterly direction. The proportion of males that dispersed was higher than that of females, but the difference was not statistically significant. All juveniles dispersing did so before they were one year old. The bimodal timing of dispersal in summer and late winter to early spring reflected an underlying similar pattern of breeding. Most possums made several moves before settling. A higher proportion of possums dispersed from the lowdensity area of pastoral and cropping land than from the higher-density areas of swamp and willows. A few dispersal records of ear-tagged animals were also obtained; most records were of males from the area of pastoral and cropping land, and movements ranged from 3 to 25 km.

Understanding animal movements that underpin ecosystem processes is fundamental to ecology. Recent advances in animal tags have increased the ability to remotely locate larger species; however, this technology is not suitable for up to 70% of the world’s bird and mammal species. The most widespread technique for tracking small animals is to manually locate low-power radio transmitters from the ground with handheld equipment. Despite this labor-intensive technique being used for decades, efforts to reduce or automate this process have had limited success. Here, we present an approach for tracking small radio-tagged animals by using an autonomous and lightweight aerial robot. We present experimental results where we used the robot to locate critically endangered swift parrots (Lathamus discolor) within their winter range. The system combines a miniaturized sensor with newly developed estimation algorithms to yield unambiguous bearing- and range-based measurements with associated measures of uncertainty. We incorporated these measurements into Bayesian data fusion and information-based planning algorithms to control the position of the robot as it collected data. We report estimated positions that lie within about 50 meters of the true positions of the birds on average, which are sufficiently accurate for recapture or observation. Further, in comparison with experienced human trackers from locations where the signal was detectable, the robot produced a correct estimate as fast or faster than the human. These results provide validation of robotic systems for wildlife radio telemetry and suggest a way for widespread use as human-assistive or autonomous devices.

Unmanned aerial vehicles (UAVs) or drones have rapidly evolved to enable carrying various sensors such as thermal sensors for vision or antennas for radio waves. Therefore, drones can be transformative for applications such as surveillance and monitoring because they have the capability to greatly reduce the time and cost associated with traditional tasking methods. Realising this potential necessitates equipping UAVs with the ability to perform missions autonomously. This dissertation considers the problems of online path planning for UAVs for the fundamental task of surveillance comprising of tracking and discovering multiple mobile objects in a scene. Tracking and discovering an unknown and time-varying number of objects is a challenging problem in itself. Objects such as people or wildlife tend to switch between various modes of movements. Measurements received by the UAV’s on-board sensors are often very noisy. In practice, the on-board sensors have a limited field of view (FoV), hence, the UAV needs to move within range of the mobile objects that are scattered throughout a scene. This is extremely challenging because neither the exact number nor locations of the objects of interest are available to the UAV. Planning the path for UAVs to effectively detect and track multi-objects in such environments poses additional challenges. Path planning techniques for tracking a single object are not applicable. Since there are multiple moving objects appearing and disappearing in the region, following only certain objects to localise them accurately implies that a UAV is likely to miss many other objects. Furthermore, online path planning for multi-UAVs remains challenging due to the exponential complexity of multi-agent coordination problems. In this dissertation, we consider the problem of online path planning for UAV-based localisation and tracking of multi-objects. First, we realised a low cost on-board radio receiver system on aUAV and demonstrated the capability of the drone-based platform for autonomously tracking and locating multiple mobile radio-tagged objects in field trials. Second, we devised a track-before-detect filter coupled with an online path planning algorithm for joint detection and tracking of radio-tagged objects to achieve better performance in noisy environments. Third, we developed a multi-objective planning algorithm for multi-agents to track and search multi-objects under the practical constraint of detection range limited on-board sensors (or FoV limited sensors). Our formulation leads to a multi-objective value function that is a monotone submodular set function. Consequently, it allows us to employ a greedy algorithm for effectively controlling multi-agents with a performance guarantee for tracking discovered objects while searching for undiscovered mobile objects under practical constraints of limited FoV sensors. Fourth, we devised a fast distributed tracking algorithm that can effectively track multi-objects for a network of stationary agents with different FoVs. This is the first such solution to this problem. The proposed method can significantly improve capabilities of a network of agents to track a large number of objects moving in and out of the limited FoV of the agents’ sensors compared to existing methods that do not consider the problem of unknown and limited FoV of sensors.
Thesis (Ph.D.) -- University of Adelaide, School of Computer Science, 2020

The term RFID refers to radio frequency identification and describes transponders or tags that are attached to animate or inanimate objects and are automatically read by a network infrastructure or networked reading devices. Current solutions such as optical character recognition (OCR), bar codes, or smart card systems require manual data entry, scanning, or readout along the supply chain. These procedures are costly, timeconsuming, and inaccurate. RFID systems are seen as a potential solution to these constraints, by allowing non-line-of-sight reception of the coded data. Identification codes are stored on a tag that consists of a microchip and an attached antenna. Once the tag is within the reception area of a reader, the information is transmitted. A connected database is then able to decode the identification code and identify the object. Such network infrastructures should be able to capture, store, and deliver large amounts of data robustly and efficiently (Scharfeld, 2001). The applications of RFID in use today can be sorted into two groups of products: • The first group of products uses the RFID technology as a central feature. Examples are security and access control, vehicle immobilization systems, and highway toll passes (Inaba & Schuster, 2005). Future applications include rechargeable public transport tickets, implants holding critical medical data, or dog tags (Böhmer, Brück, & Rees, 2005). • The second group of products consists of those goods merely tagged with an RFID label instead of a bar code. Here, the tag simply substitutes the bar code as a carrier of product information for identification purposes. This seems sensible, as RFID tags display a number of characteristics that allow for faster, easier, more reliable, and superior identification. Once consumers are able to buy RFID tagged products, their attitude toward such tags is of central importance. Consumer acceptance of RFID tags may have severe consequences for all companies tagging their products with RFID.