| KEYWORD |
Sensor system for monitoring physical and chemical parameters in artesian wells
keywords DESIGN AND BUILD, ROBOTICS
Reference persons DANIELA MAFFIODO, TERENZIANO RAPARELLI
Research Groups 04-Automazione e Robotica
Thesis type DESIGN, DESIGN AND EXPERIMENTS
Description The proposed thesis is in the context of a complex research topic: the problem of accidents due to children falling into the well (at least two per year worldwide), a very current issue following the increasing number of artesian wells due to the desertification of the planet. The outcome is always inauspicious as it is not possible to extract the child, in a timely manner, from a cramped and hostile environment, characterized by low temperatures and high humidity, in which it is impossible to survive for more than a few hours. The extraction intervention involves digging a parallel well in an attempt to reach the depth where the child is.
This project aims to develop equipment to intervene in a timely manner by bringing, at first, refreshment (warm air and refreshing and nutritious liquids) and, at the same time, stabilization of the child at the elevation where he or she is and then extracting the baby. The extraction phase is the most difficult because the baby is often stuck and the space is cramped.
The extraction device proposed here is based on an innovative remote manipulation robot with immersive vision, the result of a collaboration between robotics and virtual reality technologies, which allows it to operate in the well, where access is not possible, with the child's assessment, decision and control.
The activity proposed in this thesis consists of the design in the assembly and subsequent laboratory testing of a sensor system for parameter acquisition. Specifically, it will be necessary to design a test environment in which parameters of ambient temperature, humidity, oxygen content, and others are monitored and then acquired with a sensor system (previously designed) that will be installed in the future on board the mobile well rescue robot.
Deadline 15/03/2025
PROPONI LA TUA CANDIDATURA