Smart_Safe: AI-Driven Safety System for Indoor Industrial Environments Using Wearable and Auto-ID

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27350%2F25%3A10259317" target="_blank" >RIV/61989100:27350/25:10259317 - isvavai.cz</a>

Výsledek na webu

<a href="https://ieeexplore.ieee.org/document/11206248" target="_blank" >https://ieeexplore.ieee.org/document/11206248</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/MASS66014.2025.00081" target="_blank" >10.1109/MASS66014.2025.00081</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Smart_Safe: AI-Driven Safety System for Indoor Industrial Environments Using Wearable and Auto-ID

Popis výsledku v původním jazyce

This poster presents the Smart_Safe system, a modular platform for real-time safety management in indoor industrial environments. The system integrates wearable sensors, Auto-ID technologies (such as RFID and Bluetooth), and AI-based analytics to detect, evaluate, and prevent occupational safety risks. Its core functionality includes real-time tracking of workers, detection of critical events (such as falls or zone violations), and prevention of collisions between people and mobile robots or forklifts. The system is designed to be scalable, interoperable with existing infrastructure, and privacy-respecting through the use of anonymized tracking and local processing. Integration with edge computing and digital twins enables context-aware decision-making and dynamic response to incidents. Smart_Safe supports applications in warehouses, smart factories, and production halls with a focus on high-risk or high-traffic areas. Initial testing demonstrates the feasibility of using hybrid sensor networks and lightweight AI models to ensure workplace safety and optimize movement flows. The poster also outlines the international collaboration between Czech and Korean partners, highlighting the hardware-software co-design process and the future roadmap for deployment.

Název v anglickém jazyce

Smart_Safe: AI-Driven Safety System for Indoor Industrial Environments Using Wearable and Auto-ID

Popis výsledku anglicky

This poster presents the Smart_Safe system, a modular platform for real-time safety management in indoor industrial environments. The system integrates wearable sensors, Auto-ID technologies (such as RFID and Bluetooth), and AI-based analytics to detect, evaluate, and prevent occupational safety risks. Its core functionality includes real-time tracking of workers, detection of critical events (such as falls or zone violations), and prevention of collisions between people and mobile robots or forklifts. The system is designed to be scalable, interoperable with existing infrastructure, and privacy-respecting through the use of anonymized tracking and local processing. Integration with edge computing and digital twins enables context-aware decision-making and dynamic response to incidents. Smart_Safe supports applications in warehouses, smart factories, and production halls with a focus on high-risk or high-traffic areas. Initial testing demonstrates the feasibility of using hybrid sensor networks and lightweight AI models to ensure workplace safety and optimize movement flows. The poster also outlines the international collaboration between Czech and Korean partners, highlighting the hardware-software co-design process and the future roadmap for deployment.

Druh

D - Stať ve sborníku

CEP obor

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OECD FORD obor

20202 - Communication engineering and systems

Projekt

<a href="/cs/project/LUE231026" target="_blank" >LUE231026: Inteligentní systém řízení bezpečnosti pro průmyslová prostředí založený na umělé inteligencí a Auto-ID</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2025

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

2025 IEEE 22nd International Conference on Mobile Ad-Hoc and Smart Systems, MASS 2025 : proceedings : 6-8 October 2025, Chicago, Illinois, United States

ISBN

979-8-3315-6600-5

ISSN

2155-6806

e-ISSN

2155-6814

Počet stran výsledku

2

Strana od-do

510-511

Název nakladatele

IEEE

Místo vydání

Piscataway

Místo konání akce

Chicago

Datum konání akce

6. 10. 2025

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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