Publicação

System for Managing Cat Shelters and Monitoring Clinical Signs

Ver documento

Detalhes bibliográficos
Resumo:Most cat shelters in Portugal (and more) are overcrowded, besides they rely on volunteers that aren’t there everyday or even every week, so it becomes impossible to note every out of the ordinary behavior in every cat there. Due to this fact it is very complicated to rapidly detect sickness in a cat leading to propagation of the disease in the shelter. With the available technology it would be interesting to have an application where any volunteer could register a cats sign, from a simple sneeze to tears. Using this information the system would then analyze the database and verify if this cat has a set of signs that would link it to a common disease. If so, it would alert the responsible that could then check the animals well being. This dissertation begins with research in previously published studies, ranging from pet symptom checkers and machine learning accuracy, to animal shelter management applications, optimal shelter conditions and common feline diseases. Following this, the application for managing the cat shelter is developed, in this app, that is available as a mobile app aswell as aweb app, it is possible to register all the cats in the shelter aswell as clinical signs shown by them. This was meant to build a lengthy database that would then allow for the disease prediction to be developed. Due to the fact that this process requires a long period of time, this feature was not yet developed. Nevertheless, a simpler interface was implemented linking the most common clinical signs to the most common diseases. Furthermore, a data acquisition device was developed with a temperature and humidity sensor for data collection, as well as a bluetooth module that allowed for communication with the app. Using this information it can then be determined whether these factors are relevant in the manifestation and propagation of disease in cat shelters.
Autores principais:Melo, Maria Coelho Bento de
Assunto:Cat Shelters Application Management Monitoring Clinical Signs Data Acquisition Device
Ano:2022
País:Portugal
Tipo de documento:dissertação de mestrado
Tipo de acesso:acesso aberto
Instituição associada:Universidade Nova de Lisboa
Idioma:inglês
Origem:Repositório Institucional da UNL

Registos relacionados

Registos relacionados