Dettagli Bibliografici
| Autore principale: |
Chiconetto, Cássio |
| Data di pubblicazione: |
2025 |
| Natura: |
Master thesis
|
| Lingua: |
por |
| Fonte: |
Repositório Institucional da UPF |
| Download full: |
https://repositorio.upf.br/handle/123456789/10017
|
Riassunto: |
This paper presents the development of a technological solution based on mobile computing to optimize technical deliveries and maintenance of agricultural machinery. The research arises from the need for Agriculture 4.0 to reduce time and human resources in procedures that traditionally require more than one technician present. The research methodology was based on studies of wireless communication for the Internet of Things and resulted in the creation of an application for Android devices using React Native. This application connects to the machine’s electronic system using Bluetooth Low Energy as a means of communication, interacting with the Human-Machine Interface (HMI) via the CAN Bus. A new communication protocol was developed to complement the existing Bluetooth protocols at the company where the solution was developed. The solution aims to allow a technician to remotely control booms and the spraying system on a self-propelled machine. The interface was developed considering the harsh conditions of the agricultural environment, using graphical elements similar to HMI, thus maintaining compatibility with existing systems and preserving established safety rules. Validation tests were performed progressively on a scale until reaching the actual machine. The modular architecture allows future expansions to other types of agricultural machinery, consolidating the foundation for similar applications in the context of the Internet of Things for Agriculture. To validate usability, the System Usability Scale was applied, along with objective and qualitative questions, with employees of the company where the solution was developed. The results serve as a parameter for improving the solution, which aims to contribute to operational efficiency in precision agriculture, seeking to reduce technical support times. |