The motivation of the BATS project is to provide new methodologies for efficient and effective tracking of bats in their natural habitat. Particularly, as an application example, this research project focuses on bats, which are one of the most protected species in the European Union. The developed tracking system for capturing and automatic processing of bats motions should meet a few specific requirements: First, it has to be individual-based, that is, tracing data should be assignable to a particular bat. Second, localization of bats has to be performed with high precision, and third, any contact or interaction between two different bats has to be accounted. For instance, it is asked to make clear statements about the duration female bats are nursing their youngs, but also to study their hunting and general social behavior. Matters like that can only be tracked when mobile sensor nodes are directly mounted on each bat. These kind of nodes need to communicate with both static sensor nodes on the ground, which are distributed among the whole compound, and other mobile nodes.
Fulfilling such requirements and maintaining key aspects such as heterogeneity, scalability, adaptivity, and energy-awareness is a challenging task because of implicitly resulting strict limitations. For instance, the maximum weight the examined bat species can carry amounts to 2g (up to ten percent of its own body weight). Hence, this weight must not be exceeded by the mobile sensors that are mounted on the bats (including batteries, circuits, and antennas). All in all, the mobile nodes should be optimized for
As a consequence thereof, such requirements limit available memory and computation power. Subsequently, hardware components have to be selected wisely and custom circuits need to be synthesized. Doing so, however, not only requires to have energy-aware and adaptive hardware but also protocols and software in general. For this, distributed ad-hoc memory and computation power must be localized and used in an efficient manner. For example, optimal energy management can be achieved by means of pre-aggregation of collected data on the nodes, which is combined with intelligent routing mechanisms that allow for efficient data transfer between all mobile and static nodes.
Solving problems like that is the reason why this research project has been initiated. People with different specialities and orientations are encouraged to work together to find most appropriate solutions. In the end, they will smooth the way for new possible applications in the fields of ecology, biomedicine, behavioral biology, and evolutionary biology.
This sub project's main goal is to provide a flexible system software infrastructure, called ARTE (Adaptive Run-Time Environment for Resource-scarce Sensor Systems). A major challenge is the restricted availability of resources, such as energy and memory, but also ad-hoc network connections. The software infrastructure requires specialized tools for monitoring energy demand and also new techniques to save energy to ensure long runtimes of the node.
In Brunswick, we focus on the development of the system software, running on an animal-borne mobile-node. Key of the development is to conserve as much energy as possible to prolong the runtime and to acquire as much data as possible. However, providing such kind of application requires besides the application itself also software which is able to decode received data and tool support for the biologist to enable reconfiguration on demand. Parts of the systems are already tested successfully in a field test in Gamboa (Panama) which lasts more than 2 month. This test showed, that our software fulfills the requirements of runtime and functionality to provide biologically relevant data.
Now, the second phase is started and focuses on different improvements in terms of energy awareness and functionality like reconfiguration. In sum, the system shall be scaled up to 60 Bats, which raises new questions like how to perform synchronization in an energy efficient way and also how to deal with a huge amount of data which must be transferred to the base-stations network. Scaling up the system enables biologists to observe bigger group sizes like the Desmodus rotundus, a highly social species, which also shares food among group members in their roosts. Tracking this species, will give a deeper insight into the social networks and structure of these individuals.
In upcoming field tests Forchheim (July, 2017) and Panama (September, 2017) the system should be tested intensively and acquire more data than the system before.
| Title | Type | Supervisor | Status |
|---|---|---|---|
| Development of a Memory Controller in Gem5 | Master Thesis | Dr. Björn Cassens | finished |
| Implementation of Simulation Markers in Gem5 | Bachelor Thesis | Dr. Björn Cassens | finished |
| System Support for Instant On/Off Switching Utilizing NVRAM | Bachelor Thesis | Dr. Björn Cassens | finished |
| Aufbau zur Untersuchung der Einflüsse durch die Nutzung unterschiedlicher Speicher Technologien | Bachelor Thesis | Dr. Björn Cassens | finished |
| Implementierung eines FPGA basierendes High-Speed Debugging Interfaces | Master Thesis, Project Thesis | Dr. Björn Cassens | finished |
| Erweiterung der Typunterstützung innerhalb des SEEP-Frameworks um Datenstrukturen | Bachelor Thesis | Dr. Björn Cassens | finished |
| Implementierung einer FPGA basierenden Datenakquisition | Bachelor Thesis, Master Thesis, Project Thesis | Dr. Björn Cassens | cancelled |
This research project is funded by the German Research Foundation (DFG) under grants no. FOR 1508 (subproject TP2).