In this study, we propose the concept of AI-assisted bio-loggers, which we will refer to as AI on Animals (AIoA), that can use low-cost (i.e., non-resource-intensive) sensors to automatically detect behaviours of interest in real time, allowing them to conditionally activate high-cost (i.e., resource-intensive) sensors to target those behaviours. This is especially true when working with animals such as birds, since the mass of a bio-logger is restricted to a small fraction of the bird’s mass 8, e.g., the video bio-loggers used in this study weighed as little as 27 g (“Methods”), which greatly restricts the maximum battery capacity.
However, these data collection strategies fall short when attempting to collect data using resource-intensive sensors (e.g., video cameras) from specific animal behaviours, as they tend to deplete all of the bio-loggers’ resources on non-target behaviours 18, 19. Although there have been extraordinary improvements in the sensors and storage capacities of bio-loggers since the first logger was attached to a Weddell seal 4, 5, 6, 7, 8, 9, their data collection strategies have remained relatively simple: record data continuously, record data in bursts (e.g., periodic sampling), or use manually determined thresholds to detect basic collection criteria such as a minimum depth, acceleration threshold, or illumination level 10, 11, 12, 13, 14, 15, 16, 17. Our work will provide motivation for more widespread adoption of AI in bio-loggers, helping us to shed light onto until now hidden aspects of animals’ lives.Īnimal-borne data loggers, i.e., bio-loggers, have revolutionised the study of animal behaviour in the animals’ natural environments, allowing researchers to gain great insights into various aspects of the animals’ lives, such as their social interactions and interactions with their environments 1, 2, 3. We demonstrate our method on bio-loggers attached to seabirds including gulls and shearwaters, where it captured target videos with 15 times the precision of a baseline periodic-sampling method. This study proposes using AI on board video-loggers in order to use low-cost sensors (e.g., accelerometers) to automatically detect and record complex target behaviours that are of interest, reserving their devices’ limited resources for just those moments. However, bio-loggers have short runtimes when collecting data from resource-intensive (high-cost) sensors. Bio-logging allows us to observe many aspects of animals’ lives, including their behaviours, physiology, social interactions, and external environment. The ergonomic logger case is weather-resistant and features a rubber seal that serves as a shock cushion between the two halves.Unravelling the secrets of wild animals is one of the biggest challenges in ecology, with bio-logging (i.e., the use of animal-borne loggers or bio-loggers) playing a pivotal role in tackling this challenge. In addition, configurations and sensor calibration data can be transferred to a computer and then shared with other LI-1500 units. When attached to a computer, the logger acts as a mass-storage device with a simple drag-and-drop file system.
Light logger bird free#
Graph large data sets using LI-COR’s free FV7x00 software. Raw Mode sampling collects samples at up to 500 Hz from one sensor and is ideal for high frequency applications. With Standard Modes sampling, the logger collects samples at up to 20 Hz from up to three sensors at once, and math operations and averaging can be applied to the data.
Logging can be done manually, or menus can be used to set up one-time, daily, or continual measurement routines. Attach your choice of LI-COR Quantum sensors (sold separately) to the logger’s three BNC connectors. A GPS version of the LI-1500 is also available. This light sensor logger features a menu-driven interface, 1 GB of flash memory, and a USB interface for easy data transfer. GPS data can be logged independently or with light data. Logger features a built-in GPS that records the location of measurements and facilitates repeated visits to the same location for tracking light levels over time. LI-COR LI-1500 Light Sensor Logger with GPS
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