SMARTGRID is an innovative project funded by INAIL, aimed at developing and implementing advanced technologies to enhance safety in workplaces, particularly in complex environments where human operators and remotely controlled mobile machines operate simultaneously. SMARTGRID is an innovative project that merges cutting-edge technology with workplace safety.
The project results from a collaboration between leading academic and institutional entities: INAIL, the University of Pisa, the University of Tuscia, and the University of Salento, under a
To integrate its advanced solutions into an autonomous robotic platform, the University of Pisa research team collaborated with Aitronik, seeking to leverage the company’s expertise. SMARTGRID is an innovative project that benefits from this collaboration.
Project Phases
SMARTGRID was structured into two main phases:
- Creation of a functional prototype system that operates without relying on beacon-based localization technologies.
- Deployment of the complete system, incorporating advanced localization technologies and achieving optimized performance.
Project Focus: Human-Machine Detection
The project focuses on swiftly and precisely detecting human presence near mobile machinery, aiming to prevent accidents and enhance safe interactions between humans and robots. SMARTGRID is an innovative project ensuring that these interactions are safe and effective.
To achieve this, the system employs passive RFID tags attached to both operators and machines. The behavior and performance of these tags are highly dependent on Tag Sensitivity, but it is crucial to consider the effectiveness of the entire RFID system, composed of:
- Antenna
- RFID Chip
- Tagged Object
These three components must work in synergy to ensure timely and effective detection.
Localization Technologies Employed
The SMARTGRID system integrates multiple localization technologies, each selected for its specific advantages:
- Passive UHF RFID – for non-intrusive, low-energy tracking.
- Bluetooth Low Energy (BLE) – for ease of implementation and the widespread availability of compatible devices.
- Ultra Wide Band (UWB) – to provide high-precision localization, which is essential in dynamic and critical environments.
Experimentation and Results
The project team deployed a mobile robot equipped with detection and localization modules, integrating RFID technologies developed by the Department of Information Engineering (DII). The combined hardware and software integration enabled real-time signal processing to determine the relative position between human operators and machines. SMARTGRID is an innovative project that highlights the capability of these technologies when implemented effectively.
On September 22, 2023, a public demonstration of the system was held at the “Nello Lupori” Experimental and Educational Agricultural Company of the University of Tuscia. The event was attended by academics, technical experts, and institutional representatives, including:
- Samuele Cardella, Engineer (Aitronik srl)
- Dr. Roberto Mati (Aitronik srl)
- Dr. Andrea Motroni (University of Pisa)
- Prof. Roberto Gabrielli (Project Lead, University of Pisa)
- Prof. Danilo Monarca (University of Tuscia)
- Prof. Paolo Nepa (University of Pisa)
- Prof. Luca Landi (University of Perugia)
- Prof. Luca Catarinucci and Prof. Luigi Patrono (University of Salento)
- Marco Pirozzi, Engineer (INAIL Project Coordinator)
- Luciano Di Donato, Engineer; Alessandro Ferraro, Engineer; Laura Tommasini, Engineer (INAIL Operational Unit)
The event showcased both the operational readiness and the effectiveness of the developed solution in improving the interaction between machines and field operators.
Project Impact
The main outcome of the SMARTGRID project has been a substantial improvement in the safety of ground staff, thanks to the robots’ real-time detection of operator positions relative to the machines. This functionality allows the system to prevent collisions and mitigate potentially hazardous situations, thus promoting a safer working environment even in highly automated settings.
