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Autonomous Sensing For Trains In The IoT Era

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Short Description

A new generation of Information Technology is revolutionizing products and people’s everyday life. Sensors and wearable technologies, in particular, are gaining popularity, with people surrounded by everything “smart,” from smart houses to smartphones, from smart trains to smart cities. However present-day sensor devices are mainly battery-powered and due to limited energy, they are simple with limited computational capabilities or they need to be recharged every day or even hours and thus they miss the expectations for a truly unobtrusive user experience. The proposed projects will explore theoretical limitations as well as design methods for this new kind of distributed smart sensors under extreme constraint of tiny energy buffers (batteries). Specifically, the project aims to study and develop the basis for low-power/autonomous systems for distributed smart sensors for trains and railways applications in collaboration with Bombardier that (i) can go in a zero-power but with change status fast when important events are detected (ii) have long lifetime and where possible be self-sustaining, (iii) adopts artificial intelligence connecting buildings, trains, users, wearable devices achieving true ambient intelligence. The project will address the challenges of intelligence in the face of low energy and long lifetime. One of the main expected result is on the investigation and development of novel zero-power sensors that act as a trigger for the rest of the system when an important event is detected and consume zero-power between two detections. Other important results will be provided by the combination of hardware and software co-design to achieve the ambitious goal of placing the smart sensor never recharge it. This goal will be achieved by developing novel hardware, sensors, energy harvesting and devising low-power techniques for data computation, machine learning, communication. Finally, the novel aspects of the project will be demonstrated on a sensors network running exemplar critical applications from wearable and buildings domains achieving autonomous self-sustainable in real in-field applications.

The hardware and software load of the thesis will be balanced according with the skills and preferences of the candidate students when the details task description will be provided before the student project will start. In field, measurements of the system will be performed from the students as important activity in order to evaluate power consumption, reliability, functionality, classification accuracy and energy efficiency and to further optimize the system.

The master or semester project will be developed in close collaboration with Bombardier, the Oerlikon (ZH) Lab.

Depending on the applicant's profile and project type, his tasks may involve some of the following:

  • lab. testing/characterization of the existing prototype: verification of the prototype's characteristics w.r. design specification (simulations), measuring power-consumption, and assessing detection performance in lab. Conditions
  • High-level software programming, machine learning, wireless communication
  • programming the circuit for a specific application, field testing, data acquisition

Status: Available

  • Looking for Semester and Master Project Students
Supervisors: Michele Magno Philipp Mayer


(not all need to be met by the single candidate)

  • Experience using the laboratory instrumentation - signal generators, oscilloscopes, DAQ cards, Matlab etc.
  • analog electronics and signal conditioning with operational amplifiers: amplifiers, filters, integrators etc. (not mandatory)
  • knowledge of microcontroller programming and PC programming (C/C++, preferably microcontroller with Bluetooth Low Energy but it is not mandatory)
  • basic knowledge on signal processing is a plus.
  • plus is knowledge on printed circuit board (PCB) using Altium.


30% Theory
50% Implementation
20% Testing


Luca Benini

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Detailed Task Description


Practical Details