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. 2025 Jan 3;20(1):e0312553.
doi: 10.1371/journal.pone.0312553. eCollection 2025.

The use of miniaturised Bluetooth Low Energy proximity loggers to study contacts among small rodents in agricultural settings

Florian Huels  1 , Bram Vanden Broecke  2 , Vincent Sluydts  2 , Lucinda Kirkpatrick  2   3 , Ivan Herrera Olivares  3 , Hendrik Ennen  1 , Dries Vermeiren  2 , Herwig Leirs  2   3 , Jens Jacob  1
Affiliations

The use of miniaturised Bluetooth Low Energy proximity loggers to study contacts among small rodents in agricultural settings

Florian Huels et al. PLoS One. .

Abstract

Small rodents can cause problems on farms such as infrastructure damage, crop losses or pathogen transfer. The latter threatens humans and livestock alike. Frequent contacts between wild rodents and livestock favour pathogen transfer and it is therefore important to understand the movement patterns of small mammals in order to develop strategies to prevent damage and health issues. Miniaturised proximity loggers are a newly developed tool for monitoring spatial behaviour of small mammals. The strength of the Bluetooth Low Energy (BLE) signal can be used as an indicator of close contacts between wild rodents and livestock feeding sites, which is relevant for identifying possible transmission routes. This method study focussed on the use of the technology in an agricultural setting as well as dry runs for testing and calibrating this technology in farming environments used for animal husbandry. Results show that the battery life of the loggers was mainly influenced by the pre-set scan interval. Short scan intervals resulted in reduced battery lifespan and should be maximised according to the activity patterns of the target species. Habitat affects BLE signal strength resulting in higher signal strength indoors than outdoors. The height of the location of the loggers positively affected signal strength in livestock stables. Signal reception generally decreased with increasing distance and differed among loggers making calibration necessary. Within habitat specific distances, BLE proximity logging systems can identify contacts among small mammals and between animals and particular structures of interest. These results support the use of BLE based systems in animal husbandry environments and contribute to a body of evidence of validated techniques. In addition, such approaches can provide valuable insights into possible pathogen transmission routes.

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Conflict of interest statement

I have read the journal’s policy and the authors of this manuscript have the following competing interests: Ivan Herrera Olivares, Lucinda Kirkpatrick and Herwig Leirs declare a potential conflict of interest in relation to the loggers used in the study. The devices used in this study were early prototypes of ProxLogs that were developed at and with the support of the University of Antwerp. Loggers were provided at cost price and extensive support into how to use the loggers and design the study was provided by LK and IHO. Since the study was conducted, IoSA BV has been established as a start-up company with IHO, LK and HL as founder members. IoSA BV develops and markets miniature animal trackers using on Bluetooth Low Energy technology that are based on the proximity loggers used in this study. Our involvement in the research was primarily in a supportive capacity, offering technical guidance and logistical support concerning the use of the proximity loggers. We supplied information on how to best use the loggers in the field but have made concerted efforts to minimize our influence on the study’s analysis, and interpretation of data to prevent any bias that might arise from our commercial interests. All analysis was carried out by FH and BvB who conceived of the study together with JJ, collected and analysed the data and drafted the manuscript. LK and IHO provided input in terms of how the system operates and revised the manuscript. This approach was adopted to maintain the integrity of the research process and ensure that the findings presented are the result of unbiased scientific inquiry. This declaration is made in the interest of full transparency and in accordance with the ethical guidelines of the journal and the author’s institutions.

Figures

Fig 1
Fig 1. ProxLogs Bluetooth logger system components.
Elements of the ProxLogs Bluetooth logger system, (a) mobile logger (rats): as delivered (right), sealed left; (b) stationary logger: as delivered (left), in protective case (right); (c) gateway: in protective hard case.
Fig 2
Fig 2. Calibration setup.
Experimental setup for the calibration test: placement of one stationary logger (▲) and three mobile loggers (●) in each of the seven occupied stable compartments. The stationary logger in stable IV did not record data for unknown reasons but the mobile loggers in stable IV worked.
Fig 3
Fig 3. Battery charge.
Battery charge of mobile loggers over 14 days for scan intervals 10, 30, 60 s without, with hibernation mode (H), and for a logger advertising only without scanning (Adv). Error bars are standard error. Different capital letters A-K below the figure heading and behind the scan intervals in the legend indicate a statistically significant difference between different letters. Battery charge percentage is calculated by the ProxLogs app based on battery voltage and is an estimation.
Fig 4
Fig 4. Habitat test.
a) Mean RSSI (grey circles) and b) mean number of data points (black circles) per distance in equipment shed and grassland. Error bars are standard error. Different capital letters A-B below the figure heading indicate a statistically significant difference between different letters.
Fig 5
Fig 5. Calibration test.
Mean RSSI (a) and mean number of data points (b) over distance. Error bars are standard error. Different letters below the figure heading indicate a significant difference between units.
See this image and copyright information in PMC

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