What is the project
This project develops recyclable cellulose (paper-based) pressure sensors for retail shelf monitoring. It is intended for retailers that need real-time visibility of product presence and location on shelves. The goal is to replace traditional load sensors that require complex installation and generate electronic waste (e-waste).
Project at a glance
Focus: Patented paper-based pressure sensors for sustainable retail shelf monitoring and real-time inventory intelligence (Artificial Intelligence, AI, via cloud-based algorithms)
Key demonstrators: Recyclable cellulose based pressure sensors and real-time counting interface; SmartShelf AI
Operation: Retail shelf monitoring and inventory alerts
Primary pilot locations: Retail stores
Objectives
- Detect product presence and location through pressure changes.
- Convert shelf activity into real-time inventory intelligence using cloud-based Artificial Intelligence (AI) algorithms.
- Retrofit onto existing shelves in minutes
- Reduce electronic waste (e-waste) compared with traditional load sensors.
- Support stock-level tracking and predictive restocking alerts.
What we delivered
Paper-based pressure sensors were developed to monitor retail shelves by detecting product presence and location via pressure changes, with shelf activity processed into real-time inventory intelligence using cloud-based Artificial Intelligence (AI) algorithms; the flexible sensors are designed to retrofit onto existing shelves, combining printed conductive materials with machine learning to track stock levels, and generate predictive restocking alerts, while supporting a recyclable end-of-life approach aligned with circular economy principles with a total cost of ownership that is 50–75% lower than conventional smart shelf solutions.
Metrics / KPIs
Cost efficiency vs conventional smart shelf solutions
Value: Up to 50–75% lower
Notes: Internal study comparing to existing weight sensor solutions
Pilot production of pressure sensors in INCM
Value: Achieved
Notes: Several designs were printed and good results were obtained with low variability of sensor’s response
Summary
Recyclable cellulose pressure sensors enable real-time shelf monitoring by measuring pressure changes to detect product presence and location. Shelf activity is translated into inventory intelligence using cloud-based Artificial Intelligence (AI) algorithms, supporting stock visibility, event notifications, and predictive restocking alerts. The sensors are designed to retrofit onto existing shelves and aim to reduce electronic waste at end-of-life
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