Titulo Estágio
Enhancing Water Leak Detection with AI in Fiber Optic Sensors
Áreas de especialidade
Sistemas de Informação
Local do Estágio
Instituto Pedro Nunes, R. Pedro Nunes Bloco C, 3030-199 Coimbra
Enquadramento
THE COMPANY
FiberSight, a CERN startup focused on innovation for sustainability, aims to ensure reliable and cost-effective technological solutions that empower various industries in monitoring critical parameters in real-time. Our product consists of a temperature and humidity sensor designed to address several issues such as water waste in the public distribution network, optimization of water consumption in large-scale agriculture, or even the detection of infiltrations and structural problems in large constructions such as tunnels and dams.
THE PROJECT
Distributed fiber optic sensors are advanced technological systems that utilize optical fibers as sensing elements to enable real-time monitoring and measurement over long distances. These sensors make use of the intrinsic properties of optical fibers, such as their ability to transmit light signals, to detect various physical parameters including temperature, strain, pressure, vibration, and humidity. Humidity monitoring plays a crucial role in various water-related applications, including agriculture and water leakage monitoring systems. The accurate measurement of humidity levels is of utmost importance in these contexts to ensure optimal resource management. The implementation of a distributed fiber sensor offers a promising solution to reduce water waste, especially considering its scarcity and essentiality for human well-being. By enabling precise and localized monitoring of humidity, this technology can provide real-time data that aids in identifying areas of excessive moisture, optimizing irrigation practices in agriculture, and detecting water leakage in various systems.
Objetivo
This thesis proposes enhancing fiber optic sensors with Artificial Intelligence (AI) to improve water leak detection capabilities. To develop and train the AI algorithms, we will incorporate weather information such as air temperature, relative humidity, and occurrence of rain, along with the fiber optic sensor data on temperature and humidity values.
Integrating AI algorithms into our main software will improve the probability of detecting and identifying leaks in real-time with higher accuracy than relying solely on fiber optic sensor data.
Plano de Trabalhos - Semestre 1
- Understand basic concepts of Fiber Optic Sensors;
- Literature review on AI techniques for water detection leaks;
- Develop AI algorithms to analyze fiber optic sensor data and recognize patterns indicative of water leaks;
- Prepare first intermediate report.
Plano de Trabalhos - Semestre 2
- (CONTINUE) Develop AI algorithms to analyze fiber optic sensor data and recognize patterns indicative of water leaks;
- Implement software solutions to process sensor data in real-time and provide immediate feedback on leak locations.
- Evaluate the solution with real time data.
- Finalize the master's thesis report, submission of document and preparation for final thesis defence.
Condições
The workplace will be at the company's facilities.
There is the possibility to award the internship with a scholarship, according to the candidate’s profile.
Observações
During the application phase, doubts related to this proposal, namely about the objectives and conditions, must be clarified with the supervisors, via email or a meeting, to be scheduled after contact by email.
Orientador
Tiago Filipe Pimentel das Neves
tiago.neves@fibersight.pt 📩