Pet cat behavior recognition based on YOLO model

Hung, Hsiu-Te; Chen, Rung-Ching

doi:10.1109/is3c50286.2020.00107

Cited by 5 publications

(3 citation statements)

References 2 publications

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“…With the changes in people's lifestyle and social structures across the world in recent decades, many young people now choose to keep pets instead of raising children [1]. In the past, dogs were kept as pets mainly to protect the household from theft and the livestock from wild animals.…”

Section: Introductionmentioning

confidence: 99%

“…Nowadays, however, pets are kept mainly as companions. There is one pet for every three households on average [1]. The pet industry has flourished as a consequence, as is evidenced by the ubiquity of animal hospitals and pet stores.…”

Section: Introductionmentioning

confidence: 99%

“…Most office workers do not have flexible working hours, and thus can only attend to their pets when off work. To help such people remotely care for their pets, the authors develop a complete pet home monitoring system [1].…”

Section: Introductionmentioning

confidence: 99%

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Home Monitoring of Pets Based on AIoT

Sung¹,

Hsiao²

2022

Computer Systems Science and Engineering

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With technological and social development in recent decades, people have begun pursuing more comfortable lives that frequently feature household pets that are treated like members of the family. On average, one out of every three households has a pet. This has also led to the creation and growth of many businesses in the pet industry. A few companies have developed a system that allows busy office workers to remotely care for pets at home based on the Internet of Things and an intelligent adjustment function. As owners of two dogs, the authors of this study observed their pets' living habits and recorded environmental conditions that appear suitable for them. These data were then used to develop an automatic control system to care for pets. The observational data on the pets' habits and environment were written in a program in Arduino by using the ESP8266 Wi-Fi module. The module and booster module control is the switch and setting of various household appliances. According to the loop setting of the program, the system does not need to manually switch or adjust the electrical settings of the environment. Instead, the pet's living environment is assessed by using various sensors. The use of Arduino programs helps develop a system that can automatically adjust the environment to one that is most suitable for the pet's comfort.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Home Monitoring of Pets Based on AIoT

Sung¹,

Hsiao²

2022

Computer Systems Science and Engineering

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Goose Surface Temperature Monitoring System Based on Deep Learning Using Visible and Infrared Thermal Image Integration

et al. 2021

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Owing to increased biosecurity and industrial demands, the poultry houses in Taiwan are generally nonopen and closed types, with automatic environmental control and sensor equipment gradually being installed in such houses. Environmental sensors and poultry health monitoring systems are necessary to improve poultry feeding efficiency and safety. In this work, we developed a goose surface temperature monitoring system based on deep learning using visible image and integrated with infrared thermal image. This system could detect the geese in visible image and obtain the individual goose surface temperature automatically. This system consisted of an embedded system with the trained goose detection model, a visible camera, and an infrared thermal camera. The Mask R-convolutional neural network algorithm was employed to train the goose detection model by the collected goose images. The visible camera captured visible images in the poultry house, in which the geese could be identified by the trained goose detection model. The individual surface temperatures of the geese were obtained through integration of the visible and infrared thermal images. The developed monitoring systems were installed in the land and pool areas of a commercial goose house to monitor the surface temperature of the geese and achieved a precision of 97.1% and recall of 95.1%. In addition, the goose surface temperature of the pool area was observed to be lower than that of the land area. The collected individual goose surface temperature would be used as a management index to poultry house managers. Index terms -Deep learning, goose, infrared thermal image, surface temperature, visible image.

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