Fusion of GPS and Accelerometer Information for Anomalous Trajectories Detection

Navarro, Jorge; Diego, Isaac Martín de; Fernández-Isabel, Alberto; Ortega, Felipe

doi:10.1145/3312714.3312719

Cited by 5 publications

(3 citation statements)

References 10 publications

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“…To date, studies that combine GPS data and accelerometers are a very low percentage [15,68], compared to works that use single types of data. In Cabezas et al [49], as described above, an ML-based procedure to recognize multiple activities by using accelerometer and GPS data was proposed.…”

Section: Discussionmentioning

confidence: 99%

Cow Behavioural Activities in Extensive Farms: Challenges of Adopting Automatic Monitoring Systems

Mancuso

Castagnolo

Porto

2023

Sensors

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Animal welfare is becoming an increasingly important requirement in the livestock sector to improve, and therefore raise, the quality and healthiness of food production. By monitoring the behaviour of the animals, such as feeding, rumination, walking, and lying, it is possible to understand their physical and psychological status. Precision Livestock Farming (PLF) tools offer a good solution to assist the farmer in managing the herd, overcoming the limits of human control, and to react early in the case of animal health issues. The purpose of this review is to highlight a key concern that occurs in the design and validation of IoT-based systems created for monitoring grazing cows in extensive agricultural systems, since they have many more, and more complicated, problems than indoor farms. In this context, the most common concerns are related to the battery life of the devices, the sampling frequency to be used for data collection, the need for adequate service connection coverage and transmission range, the computational site, and the performance of the algorithm embedded in IoT-systems in terms of computational cost.

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Section: Discussionmentioning

confidence: 99%

Cow Behavioural Activities in Extensive Farms: Challenges of Adopting Automatic Monitoring Systems

Mancuso

Castagnolo

Porto

2023

Sensors

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“…Therefore, this work aims to propose a general procedure to recognize multiple activities based on accelerometer and GPS data. On top of this, previous studies has been restricted, so far, to the use of one of these two types of data sources for tracking animal behaviour, with only recent exceptions [16,18,44]. In this work, we explore the potential of combining data from both types of sensors to achieve a more advanced activity pattern identification.…”

Section: Discussionmentioning

confidence: 99%

“…Another interesting line for further research is exploring the formal combination of activity records from accelerometers and GPS, for instance, through information fusion techniques [44]. The validity of this approach has already been tested for the case of outlier detection.…”

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confidence: 99%

Analysis of Accelerometer and GPS Data for Cattle Behaviour Identification and Anomalous Events Detection

Cabezas

Yubero

Visitación

et al. 2022

Entropy

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In this paper, a method to classify behavioural patterns of cattle on farms is presented. Animals were equipped with low-cost 3-D accelerometers and GPS sensors, embedded in a commercial device attached to the neck. Accelerometer signals were sampled at 10 Hz, and data from each axis was independently processed to extract 108 features in the time and frequency domains. A total of 238 activity patterns, corresponding to four different classes (grazing, ruminating, laying and steady standing), with duration ranging from few seconds to several minutes, were recorded on video and matched to accelerometer raw data to train a random forest machine learning classifier. GPS location was sampled every 5 min, to reduce battery consumption, and analysed via the k-medoids unsupervised machine learning algorithm to track location and spatial scatter of herds. Results indicate good accuracy for classification from accelerometer records, with best accuracy (0.93) for grazing. The complementary application of both methods to monitor activities of interest, such as sustainable pasture consumption in small and mid-size farms, and to detect anomalous events is also explored. Results encourage replicating the experiment in other farms, to consolidate the proposed strategy.

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Unified Performance Measure for Binary Classification Problems

Redondo

Navarro

Fernández

et al. 2020

Lecture Notes in Computer Science

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Fusion of GPS and Accelerometer Information for Anomalous Trajectories Detection

Cited by 5 publications

References 10 publications

Cow Behavioural Activities in Extensive Farms: Challenges of Adopting Automatic Monitoring Systems

Cow Behavioural Activities in Extensive Farms: Challenges of Adopting Automatic Monitoring Systems

Analysis of Accelerometer and GPS Data for Cattle Behaviour Identification and Anomalous Events Detection

Unified Performance Measure for Binary Classification Problems

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