Edge Computing for Cattle Behavior Analysis (original) (raw)
Related papers
2017
Smartphones, particularly iPhones, can be relevant instruments for researchers because they are widely used around the world in multiple domains of applications such as animal behavior. iPhones are readily available on the planet, contain many sensors and require no hardware development. They are equipped with high performance inertial measurement units (IMU) and absolute positioning systems analyzing user's movements, but they can easily be diverted to analyze likewise the behaviors of domestic animals such as cattle. Using smartphones to study animal behavior requires the improvement of the autonomy to allow the acquisition of many variables at a high frequency over long periods of time on a large number of individuals for their further processing through various models and decision-making tools. Storing, treating data at the iPhone level with an optimal consumption of energy to maximize battery life was achieved by using edge computing on the iPhone. It reduced the size of the raw data by 42% on average by eliminating redundancies. The decrease in sampling frequency, the selection of the most important variables and postponing calculations to the cloud allowed also an increase in battery life by reducing of amount of data to transmit.
Journal of Ambient Intelligence and Humanized Computing, 2019
Smartphones, particularly iPhone, can be relevant instruments for researchers in animal behavior because they are readily available on the planet, contain many sensors and require no hardware development. They are equipped with high performance Inertial Measurement Units (IMU) and absolute positioning systems analyzing users' movements, but they can easily be diverted to analyze likewise the behaviors of domestic animals such as cattle. The study of animal behavior using smart-phones requires the storage of many high frequency variables from a large number of individuals and their processing through various relevant variables combinations for modeling and decision-making. Transferring, storing, treating and sharing such an amount of data is a big challenge. In this paper, a lambda cloud architecture innovatively coupled to a scientific sharing platform used to archive, and process high-frequency data are proposed to integrate future developments of the Internet of Things applied to the monitoring of domestic animals. An application to the study of cattle behavior on pasture based on the data recorded with the IMU of iPhone 4s is exemplified. Performances comparison between iPhone 4s and iPhone 5s is also achieved. The package comes also with a web interface to encode the actual behavior observed on videos and to synchronize observations with the sensor signals. Finally, the use of Edge computing on the iPhone reduced by 43.5% on average the size of the raw data by eliminating redundancies. The limitation of the number of digits on individual variable can reduce data redundancy up to 98.5%. Keywords Animals' behavior · Smart agriculture · IMU · iPhone · Lambda architecture · Precision livestock farming
Web-based cattle behavior service for researchers based on the smartphone inertial central
Procedia Computer Science, 2017
Smartphones, particularly iPhones, can be relevant instruments for researchers in animal behavior because they are readily available on the planet, contain many sensors and require no hardware development. They are equipped with high performance inertial measurement units (IMU) and absolute positioning systems analyzing users' movements, but they can easily be diverted to analyze likewise the behaviors of domestic animals such as cattle. The study of animal behavior using smartphones requires the storage of many high frequency variables from a large number of individuals and their processing through various relevant variables combinations for modeling and decision-making. Transferring, storing, treating and sharing such an amount of data is a big challenge. In this paper, a lambda cloud architecture and a scientific sharing platform used to archive and process high-frequency data are proposed. An application to the study of cattle behavior on pasture on the basis of the data recorded with the IMU of iPhones 4S is exemplified. The package comes also with a web interface to encode the actual behavior observed on videos and to synchronize observations with the sensor signals. Finally, the use of fog computing on the iPhone reduced by 42% on average the size of the raw data by eliminating redundancies. Abstract Smartphones, particularly iPhones, can be relevant instruments for researchers in animal behavior because they are readily available on the planet, contain many sensors and require no hardware development. They are equipped with high performance inertial measurement units (IMU) and absolute positioning systems analyzing users' movements, but they can easily be diverted to analyze likewise the behaviors of domestic animals such as cattle. The study of animal behavior using smartphones requires the storage of many high frequency variables from a large number of individuals and their processing through various relevant variables combinations for modeling and decision-making. Transferring, storing, treating and sharing such an amount of data is a big challenge. In this paper, a lambda cloud architecture and a scientific sharing platform used to archive and process high-frequency data are proposed. An application to the study of cattle behavior on pasture on the basis of the data recorded with the IMU of iPhones 4S is exemplified. The package comes also with a web interface to encode the actual behavior observed on videos and to synchronize observations with the sensor signals. Finally, the use of fog computing on the iPhone reduced by 42% on average the size of the raw data by eliminating redundancies.
Improvement of battery life of iPhones Inertial Measurement Unit by using edge computing
2017
Smartphones, particularly iPhones, can be relevant instruments for researchers widely used around the world in multiple domains of applications such as animal behavior. iPhones are readily available on the planet, contain many sensors and require no hardware development. They are equipped with high performance inertial measurement units (IMU) and absolute positioning systems analyzing users movements, but they can easily be diverted to analyze likewise the behaviors of domestic animals such as cattle. Using smartphones to study animal behavior requires the improvement of the autonomy to allow the acquisition of many variables at a high frequency over long periods of time on a large number of individuals for their further processing through various models and decision-making tools. Storing, treating data at the iPhone level with an optimal consumption of energy to maximize battery life was achieved by using edge computing on the iPhone. It reduced the size of the raw data by 42% on a...
Sensors
Monitoring animals’ behavior living in wild or semi-wild environments is a very interesting subject for biologists who work with them. The difficulty and cost of implanting electronic devices in this kind of animals suggest that these devices must be robust and have low power consumption to increase their battery life as much as possible. Designing a custom smart device that can detect multiple animal behaviors and that meets the mentioned restrictions presents a major challenge that is addressed in this work. We propose an edge-computing solution, which embeds an ANN in a microcontroller that collects data from an IMU sensor to detect three different horse gaits. All the computation is performed in the microcontroller to reduce the amount of data transmitted via wireless radio, since sending information is one of the most power-consuming tasks in this type of devices. Multiples ANNs were implemented and deployed in different microcontroller architectures in order to find the best b...
Collecting information on estrus in cattle using the internet of things
Arquivo Brasileiro de Medicina Veterinária e Zootecnia
Monitoring the movements of ruminant animals is one of the most challenging tasks. In animals that act according to their habits, it is difficult to label such movements and transfer them to farmers. Monitoring and recording the movement and behavior of animals on a farm is an adopted method for successfully determining the duration of the estrus cycle in ruminant animals. The Internet is a technology that offers remarkable solutions for such applications. The aim of this study is to determine the hourly step counts and to find the estrus period in the most accurate way with a circuit design applied to the ankles of animals using an IoT-supported microcontroller. The data is transferred to the web environment wirelessly and monitored via wi-fi communication signals. This wireless wearable and network equipment determines the step count and monitors the animal's abnormal body temperature. An IoT-supported microcontroller provides wireless communication, high-speed data transmissi...
IRJET- Tracking behavior and location of cattle using IoT
IRJET, 2020
Dairy products play a vital role in our day-today life; for the better production of dairy products proper cattle farming becomes necessary. In huge cattle sheds a farmer alone cannot supervise all the cows at a time, which might also lead to mislay of cows. With the illustrious use of sensors (Posture Sensor, Temperature sensor, GPS Module) connected to Arduino, the device can track cattle activities and location throughout the day. Internet of Things (IoT) provides wide range of applications through which the sensor collected cattle information can be accessed and with the help of cloud computing the collected information can be processed. This paper deals with the system which analyzes the behavior of cattle and sends it to the website which will be monitored by farm head.
Design of Scalable IoT Architecture Based on AWS for Smart Livestock
Animals, 2021
In the ecological future of the planet, intelligent agriculture relies on CPS and IoT to free up human resources and increase production efficiency. Due to the growing number of connected IoT devices, the maximum scalability capacity, and available computing power of the existing architectural frameworks will be reached. This necessitates finding a solution that meets the continuously growing demands in smart farming. Cloud-based IoT solutions are achieving increasingly high popularity. The aim of this study was to design a scalable cloud-based architecture for a smart livestock monitoring system following Agile methodology and featuring environmental monitoring, health, growth, behaviour, reproduction, emotional state, and stress levels of animals. The AWS services used, and their specific tasks related to the proposed architecture are explained in detail. A stress test was performed to prove the data ingesting and processing capability of the proposed architecture. Experimental re...
The Internet of Things enhancing animal welfare and farm operational efficiency
Journal of Dairy Research
The growth in wirelessly enabled sensor network technologies has enabled the low cost deployment of sensor platforms with applications in a range of sectors and communities. In the agricultural domain such sensors have been the foundation for the creation of decision support tools that enhance farm operational efficiency. This Research Reflection illustrates how these advances are assisting dairy farmers to optimise performance and illustrates where emerging sensor technology can offer additional benefits. One of the early applications for sensor technology at an individual animal level was the accurate identification of cattle entering into heat (oestrus) to increase the rate of successful pregnancies and thus optimise milk yield per animal. This was achieved through the use of activity monitoring collars and leg tags. Additional information relating to the behaviour of the cattle, namely the time spent eating and ruminating, was subsequently derived from collars giving further ins...