Time synchronisation for millisecond-precision on bio-loggers
Abstract Time-synchronised data streams from bio-loggers are becoming increasingly important for analysing and interpreting intricate animal behaviour including split-second decision making, group dynamics, and collective responses to environmental conditions. With the increased use of AI-based appr...
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| Format: | Article |
| Language: | English |
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BMC
2024-10-01
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| Series: | Movement Ecology |
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| Online Access: | https://doi.org/10.1186/s40462-024-00512-7 |
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| author | Timm A. Wild Georg Wilbs Dina K. N. Dechmann Jenna E. Kohles Nils Linek Sierra Mattingly Nina Richter Spyros Sfenthourakis Haris Nicolaou Elena Erotokritou Martin Wikelski |
| author_facet | Timm A. Wild Georg Wilbs Dina K. N. Dechmann Jenna E. Kohles Nils Linek Sierra Mattingly Nina Richter Spyros Sfenthourakis Haris Nicolaou Elena Erotokritou Martin Wikelski |
| author_sort | Timm A. Wild |
| collection | DOAJ |
| description | Abstract Time-synchronised data streams from bio-loggers are becoming increasingly important for analysing and interpreting intricate animal behaviour including split-second decision making, group dynamics, and collective responses to environmental conditions. With the increased use of AI-based approaches for behaviour classification, time synchronisation between recording systems is becoming an essential challenge. Current solutions in bio-logging rely on manually removing time errors during post processing, which is complex and typically does not achieve sub-second timing accuracies. We first introduce an error model to quantify time errors, then optimise three wireless methods for automated onboard time (re)synchronisation on bio-loggers (GPS, WiFi, proximity messages). The methods can be combined as required and, when coupled with a state-of-the-art real time clock, facilitate accurate time annotations for all types of bio-logging data without need for post processing. We analyse time accuracy of our optimised methods in stationary tests and in a case study on 99 Egyptian fruit bats (Rousettus aegyptiacus). Based on the results, we offer recommendations for projects that require high time synchrony. During stationary tests, our low power synchronisation methods achieved median time accuracies of 2.72 / 0.43 ms (GPS / WiFi), compared to UTC time, and relative median time accuracies of 5 ms between tags (wireless proximity messages). In our case study with bats, we achieved a median relative time accuracy of 40 ms between tags throughout the entire 10-day duration of tag deployment. Using only one automated resynchronisation per day, permanent UTC time accuracies of ≤ 185 ms can be guaranteed in 95% of cases over a wide temperature range between 0 and 50 °C. Accurate timekeeping required a minimal battery capacity, operating in the nano- to microwatt range. Time measurements on bio-loggers, similar to other forms of sensor-derived data, are prone to errors and so far received little scientific attention. Our combinable methods offer a means to quantify time errors and autonomously correct them at the source (i.e., on bio-loggers). This approach facilitates sub-second comparisons of simultaneously recorded time series data across multiple individuals and off-animal devices such as cameras or weather stations. Through automated resynchronisations on bio-loggers, long-term sub-second accurate timestamps become feasible, even for life-time studies on animals. We contend that our methods have potential to greatly enhance the quality of ecological data, thereby improving scientific conclusions. |
| format | Article |
| id | doaj-art-de0f8b51f82b4a1c9000e979f183f1c8 |
| institution | OA Journals |
| issn | 2051-3933 |
| language | English |
| publishDate | 2024-10-01 |
| publisher | BMC |
| record_format | Article |
| series | Movement Ecology |
| spelling | doaj-art-de0f8b51f82b4a1c9000e979f183f1c82025-08-20T02:18:35ZengBMCMovement Ecology2051-39332024-10-0112111310.1186/s40462-024-00512-7Time synchronisation for millisecond-precision on bio-loggersTimm A. Wild0Georg Wilbs1Dina K. N. Dechmann2Jenna E. Kohles3Nils Linek4Sierra Mattingly5Nina Richter6Spyros Sfenthourakis7Haris Nicolaou8Elena Erotokritou9Martin Wikelski10Department of Migration, Max Planck Institute of Animal BehaviorDepartment of Migration, Max Planck Institute of Animal BehaviorDepartment of Migration, Max Planck Institute of Animal BehaviorDepartment of Migration, Max Planck Institute of Animal BehaviorDepartment of Migration, Max Planck Institute of Animal BehaviorDepartment of Migration, Max Planck Institute of Animal BehaviorDepartment of Migration, Max Planck Institute of Animal BehaviorDepartment of Biological Sciences, University of CyprusRural Development and Environment, Ministry of AgricultureRural Development and Environment, Ministry of AgricultureDepartment of Migration, Max Planck Institute of Animal BehaviorAbstract Time-synchronised data streams from bio-loggers are becoming increasingly important for analysing and interpreting intricate animal behaviour including split-second decision making, group dynamics, and collective responses to environmental conditions. With the increased use of AI-based approaches for behaviour classification, time synchronisation between recording systems is becoming an essential challenge. Current solutions in bio-logging rely on manually removing time errors during post processing, which is complex and typically does not achieve sub-second timing accuracies. We first introduce an error model to quantify time errors, then optimise three wireless methods for automated onboard time (re)synchronisation on bio-loggers (GPS, WiFi, proximity messages). The methods can be combined as required and, when coupled with a state-of-the-art real time clock, facilitate accurate time annotations for all types of bio-logging data without need for post processing. We analyse time accuracy of our optimised methods in stationary tests and in a case study on 99 Egyptian fruit bats (Rousettus aegyptiacus). Based on the results, we offer recommendations for projects that require high time synchrony. During stationary tests, our low power synchronisation methods achieved median time accuracies of 2.72 / 0.43 ms (GPS / WiFi), compared to UTC time, and relative median time accuracies of 5 ms between tags (wireless proximity messages). In our case study with bats, we achieved a median relative time accuracy of 40 ms between tags throughout the entire 10-day duration of tag deployment. Using only one automated resynchronisation per day, permanent UTC time accuracies of ≤ 185 ms can be guaranteed in 95% of cases over a wide temperature range between 0 and 50 °C. Accurate timekeeping required a minimal battery capacity, operating in the nano- to microwatt range. Time measurements on bio-loggers, similar to other forms of sensor-derived data, are prone to errors and so far received little scientific attention. Our combinable methods offer a means to quantify time errors and autonomously correct them at the source (i.e., on bio-loggers). This approach facilitates sub-second comparisons of simultaneously recorded time series data across multiple individuals and off-animal devices such as cameras or weather stations. Through automated resynchronisations on bio-loggers, long-term sub-second accurate timestamps become feasible, even for life-time studies on animals. We contend that our methods have potential to greatly enhance the quality of ecological data, thereby improving scientific conclusions.https://doi.org/10.1186/s40462-024-00512-7Animal trackingMovement ecologyTelemetryWireless sensorsEmbedded systemsWiFi |
| spellingShingle | Timm A. Wild Georg Wilbs Dina K. N. Dechmann Jenna E. Kohles Nils Linek Sierra Mattingly Nina Richter Spyros Sfenthourakis Haris Nicolaou Elena Erotokritou Martin Wikelski Time synchronisation for millisecond-precision on bio-loggers Movement Ecology Animal tracking Movement ecology Telemetry Wireless sensors Embedded systems WiFi |
| title | Time synchronisation for millisecond-precision on bio-loggers |
| title_full | Time synchronisation for millisecond-precision on bio-loggers |
| title_fullStr | Time synchronisation for millisecond-precision on bio-loggers |
| title_full_unstemmed | Time synchronisation for millisecond-precision on bio-loggers |
| title_short | Time synchronisation for millisecond-precision on bio-loggers |
| title_sort | time synchronisation for millisecond precision on bio loggers |
| topic | Animal tracking Movement ecology Telemetry Wireless sensors Embedded systems WiFi |
| url | https://doi.org/10.1186/s40462-024-00512-7 |
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