PROTECHTO PRESENTS MAD

Workplace safety is still a silent emergency that finds a concrete and effective response in MAD, intelligent PPE against the consequences of falls, trips, and slips, often underestimated, but with a high potential for seriousness. Protechto S.r.l., an innovative SME founded by engineers Attilio Manni, Davide De Gregorio, and Mattia Giaretta, specializing in the development of high-tech personal protective equipment (PPE), presents MAD (Man Autosafe Device), the revolutionary smart airbag vest designed to significantly increase workplace safety, with a specific focus on protection from falls even from minimal heights (up to 2 meters). MAD is a cutting-edge device that, thanks to an advanced electronic system, constantly monitors the wearer’s stability and, in the event of a fall, inflates in just 0.25 seconds, protecting the worker from the consequences of the impact. The system is also equipped with an app that automatically sends an emergency signal with the injured person’s geolocation, ensuring rapid rescue intervention. The genesis of MAD Work has its roots in the direct experience gained 8 years ago by Davide De Gregorio as HSE Manager during a period of work abroad on an Oil & Gas construction site. Witnessing numerous serious accidents caused by even minor falls fueled in him and his future partners a strong motivation to develop a concrete solution to mitigate the consequences of such events. This awareness, developed in the field, led to the design of a wearable device that could truly make a difference in protecting workers, especially in situations where risk is perceived as minor but statistically significant. Slips, trips, and falls are a leading cause of workplace injuries across all sectors. Italian statistics, in line with European and American trends, highlight how accidental falls constitute a critical risk for workers. In particular, it has been observed that 80% of falls occur from heights less than 2 meters. MAD (Man Autosafe Device) was created as a concrete response to this “silent emergency”, offering effective and timely protection against the consequences of these falls. MAD Work therefore represents a significant innovation in the field of workplace safety thanks to the integration of an advanced system powered by artificial intelligence, capable of detecting a fall in just 250 milliseconds. In the event of a critical event, the airbag deploys rapidly, protecting vital areas of the body such as the head, back, coccyx, chest and ribs. The vest, classified as category 2 PPE and certified for high visibility, is equipped with a dedicated app that offers device and battery status monitoring functions, as well as allowing firmware updates. A distinctive feature is the automatic alert system: if the airbag inflates, the app automatically sends a message with the worker’s geolocation to three pre-set contacts, facilitating timely rescue intervention, which is especially crucial for those working alone. The airbag bag is made with technology derived from diving jackets, ensuring high resistance to pressure and effective protection in the event of an impact. The choice of high-performance and resistant materials was a priority to ensure the reliability of the device over time and in different working conditions. Artificial intelligence is a key element in MAD Work’s innovation. Developed in collaboration with the Department of Engineering for Innovation Medicine at the University of Verona, AI gives the system the ability to constantly learn and refine its fall detection capabilities, significantly increasing the level of safety offered by the vest. The algorithm, based on an advanced neural network, guarantees high accuracy in identifying dangerous situations. The effectiveness of this technology has also been recognized by the scientific community: the paper “A Lightweight CNN for Real-Time Pre-Impact Fall Detection”, born from the collaboration with the University of Verona, received the Best Paper Award in the A-Track at the Design, Automation and Test in Europe Conference (DATE) 2025. This research demonstrates how artificial intelligence applied to real-time fall detection is optimized for low-power devices, opening new frontiers for workplace safety.