DISTRIBUTED MULTI-SENSOR SYSTEMS FOR HUMAN SAFETY AND HEALTH

Informacje na temat projektu

DistriMuSe

Identyfikator umowy o grant: 101139769

DOI

10.3030/101139769

Data podpisania przez KE 28 Czerwca 2024

Data rozpoczęcia 1 Maja 2024

Data zakończenia 30 Kwietnia 2027

Finansowanie w ramach

• Digital, Industry and Space

Koszt całkowity

€ 34 764 819,75

Wkład UE

€ 11 274 522,51

Koordynowany przez

TEKNOLOGIAN TUTKIMUSKESKUS VTT OY
Finland

Periodic Reporting for period 1 - DistriMuSe (DISTRIBUTED MULTI-SENSOR SYSTEMS FOR HUMAN SAFETY AND HEALTH)

Okres sprawozdawczy: 2024-05-01 do 2025-04-30

Podsumowanie kontekstu i ogólnych celów projektu

We are surrounded by a variety of more-or-less intelligent technical devices, designed to serve you us or others. Applications onin your mobile phones, wrist-worn health sensors on your wrists, autonomous vacuum cleaners, robots on the factory floor and increasingly autonomous cars – all pledge to ease your tasks and keep usyou safe and healthy. The seamless interplay with these devices gains more importane as these devices proliferate and grow in t with the increased autonomy and pervasive presence of the devices. We expect continuously available support fromin the services they provide − yet we want them to disappear unobtrusively in the background when not needed. In order to provide support in a collaborative environment with human, physical and digital players, the technology needs to be equipped with senses to grasp human presence, their mental and physical state, their activities and their intentions. This is required to ensure human safety, safeguard their health, and allow for natural interaction. This project intends to improve sensing of human presence, behaviour and health in a collaborative or common environment by means of multi-sensor systems.
Objectives:
O1: Optimised innovative sensors and sensor systems for advanced human observation, measurement, and interaction
O2: ML-based data analytics, fusion and decision-making methodologies for (semi) real-time multi-sensor information processing
O3: Supporting distribution of computation algorithms across available resources from edge to cloud
O4: Building a comprehensive understanding of human physical health, mental state, behaviour, intentions, and safety risks
O5: Validating the technologies in human-centric use cases related to health and wellbeing monitoring and support; ensuring traffic safety especially for VRUs; safe interaction with robots and automated systems

Prace wykonane od początku projektu do końca okresu sprawozdawczego oraz najważniejsze dotychczasowe rezultaty

The main work performed and achievements can be described in relation to the objectives of the project:

O1 status: The state of the art of the sensor and sensor system technologies has been described in D1.1 as well as the project’s targeted innovation and KPI’s for measuring the progress. The initial ideas for using these sensor systems in the use cases has been described in D1.2 where initial user requirements and a high-level architecture for the systems were defined as well. An excel overview of all requirements in the various deliverables (including D1.2 D2.1 D3.1 and D4.1) was jointly collected. Partners working on sensor development described the plans in the D2.3 document, while D2.6 listed the connectivity of these sensors.
O2 status: Deliverable D1.1 also provided an overview of multi-sensor fusion and decision making technology state of the art and project targets and KPIs. Likewise D1.2 provided user requirements where the technology is expected to provide solutions. Technical requirements for the multi-sensor fusion needed for each of the pilots were collected in the D3.1 deliverable, and the work on the algorithm development was started. As pilot data is not yet available, development utilised pre-existing data where possible.
O3 status: D1.1 and D1.2 provided state of the art overviews on the platform technologies and initial user requirements. WP4 has initiated discussions in the project to facilitate the uptake of platform technologies across the various use cases to leverage the experimentation with novel approaches. While not all pilots can utilise a common platform or the same technologies, an attempt is made to map the elements to the reference architecture and learn from the advantages of different approaches (D4.2). Requirements were collected for each pilot in D4.1. Supporting the design and simulation of platforms is supported by dedicated tools, of which the initial implementation was described in D4.3.
O4 status: An overview of the current state of the art describing the advances and challenges in the application of human sensing systems in the target domains was described in D1.1. The use cases described in D1.2 further elaborate on the domain-specific challenges, that we intend to tackle in this project. WP5 has taken these reviews as input for the further definition of the use cases and make sure that the developed demonstrators will provide answers to the identified major challenges in human monitoring for health and safety in healthcare, mobility and robotics. Since applications in these domains also deal with sensitive human data including private and health data, guidelines for dealing with this type of data, provision of data security solutions as well as ethics considerations were defined in the D1.3 deliverable. This was further enhanced by the ethics guidelines in D7.6. The preparation of the pilots has been on-going, and ethical permission has been requested where necessary.
O5 status: The general overview of plans for the use cases were given in D1.2 and regular meetings for the organisation of the use cases, the validation work in the project – linked to WP5 – were organised. Preparations for validation have been done, including some technical testing of the demonstrators, but the actual pilots will only start in the next reporting period.

Innowacyjność oraz oczekiwany potencjalny wpływ (w tym dotychczasowe znaczenie społeczno-gospodarcze i szersze implikacje społeczne projektu)

The project is approaching its final - piloting - phase of the first cycle. This will be the phase, where the developed proof of concepts, integrated into demonstrators, will be tested and validated. For most pilots, the initial focus is on feasibility assessment as well as data collection for the development of algorithms and ML models. Actual evalutation results are therefore expected to be available after the next period, and results beyond the state of the art will be part of the next report.