Optimising Antenna Positioning for Maximum Coverage: The Case Study of Cattle Tracking in Austrian Alps Using Long Range (LoRa) Based Monitoring System

Welscher, Franz; Bulbul, Rizwan; Scholz, Johannes; Lederer, Peter

doi:10.1007/978-3-031-06245-2_6

“…But GSM transmissions require comparatively large chips [39,40], introduce high international roaming costs [36], and need about 29 times more energy compared to sending a Sigfox message [39]. LoRa enables even lower power consumption than Sigfox [4], but the transmission performance has only been evaluated theoretically, on livestock, or off-animal [4][5][6][7][41][42][43][44]. In stationary experiments with LoRa devices, maximum transmission ranges of up to 30 km were measured [45], but we assume a significant loss of range when devices are attached to wild animals in their natural environments, as for example vegetation types and moving bodies have notable effects on the radio signal propagation [46,47].…”

Section: Discussionmentioning

confidence: 99%

A multi-species evaluation of digital wildlife monitoring using the Sigfox IoT network

Wild

¹

,

Schalkwyk

²

,

Viljoen

³

et al. 2023

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Bio-telemetry from small tags attached to animals is one of the principal methods for studying the ecology and behaviour of wildlife. The field has constantly evolved over the last 80 years as technological improvement enabled a diversity of sensors to be integrated into the tags (e.g., GPS, accelerometers, etc.). However, retrieving data from tags on free-ranging animals remains a challenge since satellite and GSM networks are relatively expensive and or power hungry. Recently a new class of low-power communication networks have been developed and deployed worldwide to connect the internet of things (IoT). Here, we evaluated one of these, the Sigfox IoT network, for the potential as a real-time multi-sensor data retrieval and tag commanding system for studying fauna across a diversity of species and ecosystems. We tracked 312 individuals across 30 species (from 25 g bats to 3 t elephants) with seven different device concepts, resulting in more than 177,742 successful transmissions. We found a maximum line of sight communication distance of 280 km (on a flying cape vulture [Gyps coprotheres]), which sets a new documented record for animal-borne digital data transmission using terrestrial infrastructure. The average transmission success rate amounted to 68.3% (SD 22.1) on flying species and 54.1% (SD 27.4) on terrestrial species. In addition to GPS data, we also collected and transmitted data products from accelerometers, barometers, and thermometers. Further, we assessed the performance of Sigfox Atlas Native, a low-power method for positional estimates based on radio signal strengths and found a median accuracy of 12.89 km (MAD 5.17) on animals. We found that robust real-time communication (median message delay of 1.49 s), the extremely small size of the tags (starting at 1.28 g without GPS), and the low power demands (as low as 5.8 µAh per transmitted byte) unlock new possibilities for ecological data collection and global animal observation.

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“…But GSM transmissions require comparatively large chips [39,40], introduce high international roaming costs [36], and need about 29 times more energy compared to sending a Sigfox message [39]. LoRa enables even lower power consumption than Sigfox [4], but the transmission performance has only been evaluated theoretically, on livestock, or off-animal [4][5][6][7][41][42][43][44]. In stationary experiments with LoRa devices, maximum transmission ranges of up to 30 km were measured [45], but we assume a signi cant loss of range when devices are attached to wild animals in their natural environments, as for example vegetation types and moving bodies have notable effects on the radio signal propagation [46,47].…”

Section: Discussionmentioning

confidence: 99%

A multi-species evaluation of digital wildlife monitoring using the Sigfox IoT network

Wild

¹

,

Schalkwyk²,

Viljoen

³

et al. 2022

Preprint

View full text Add to dashboard Cite

Bio-telemetry from small tags attached to animals is one of the principal methods for studying the ecology and behaviour of wildlife. The field has constantly evolved over the last 80 years as technological improvement enabled a diversity of sensors to be integrated into the tags (e.g., GPS, accelerometers, etc.). However, retrieving data from tags on free-ranging animals remains a challenge since satellite and GSM networks are relatively expensive and or power hungry. Recently a new class of low-power communication networks have been developed and deployed worldwide to connect the internet of things (IoT). Here, we evaluated one of these, the Sigfox IoT network, for the potential as a real-time multi-sensor data retrieval and tag commanding system for studying fauna across a diversity of species and ecosystems. We tracked 312 individuals across 30 species (from 25 g bats to 3 t elephants) with seven different device concepts, resulting in more than 177,742 successful transmissions. We found a maximum line of sight communication distance of 280 km (on a flying cape vulture [Gyps coprotheres]), which sets a new documented record for animal-borne digital data transmission using terrestrial infrastructure. The average transmission success rate amounted to 68.3% (SD 22.1) on flying species and 54.1% (SD 27.4) on terrestrial species. In addition to GPS data, we also collected and transmitted data products from accelerometers, barometers, and thermometers. Further, we assessed the performance of Sigfox Atlas Native, a low-power method for positional estimates based on radio signal strengths and found a median accuracy of 12.89 km (MAD 5.17) on animals. We found that robust real-time communication (median message delay of 1.49 s), the extremely small size of the tags (starting at 1.28 g without GPS), and the low power demands (as low as 5.8 µAh per transmitted byte) unlock new possibilities for ecological data collection and global animal observation.

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“…On another note, [17] introduced a software-defined radio (SDR) architecture capable of processing cellular signals from both CDMA and LTE, marking a milestone in cellular-assisted navigation. In [18], a comprehensive review of the APP was conducted, and the ViehFinder system was introduced. Additionally, [19] stands out for its contribution to the state of the art in this field, providing a detailed overview of the methods and solvers employed.…”

Section: Introductionmentioning

confidence: 99%

Optimizing Antenna Positioning for Enhanced Wireless Coverage: A Genetic Algorithm Approach

Calles-Esteban,

Olmedo,

Hellín

et al. 2024

Sensors

0

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The precise placement of antennas is essential to ensure effective coverage, service quality, and network capacity in wireless communications, particularly given the exponential growth of mobile connectivity. The antenna positioning problem (APP) has evolved from theoretical approaches to practical solutions employing advanced algorithms, such as evolutionary algorithms. This study focuses on developing innovative web tools harnessing genetic algorithms to optimize antenna positioning, starting from propagation loss calculations. To achieve this, seven empirical models were reviewed and integrated into an antenna positioning web tool. Results demonstrate that, with minimal configuration and careful model selection, a detailed analysis of antenna positioning in any area is feasible. The tool was developed using Java 17 and TypeScript 5.1.6, utilizing the JMetal framework to apply genetic algorithms, and features a React-based web interface facilitating application integration. For future research, consideration is given to implementing a server capable of analyzing the environment based on specific area selection, thereby enhancing the precision and objectivity of antenna positioning analysis.

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Optimising Antenna Positioning for Maximum Coverage: The Case Study of Cattle Tracking in Austrian Alps Using Long Range (LoRa) Based Monitoring System

Cited by 4 publications

References 16 publications

A multi-species evaluation of digital wildlife monitoring using the Sigfox IoT network

A multi-species evaluation of digital wildlife monitoring using the Sigfox IoT network

A multi-species evaluation of digital wildlife monitoring using the Sigfox IoT network

Optimizing Antenna Positioning for Enhanced Wireless Coverage: A Genetic Algorithm Approach

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