Use Case: Smart Industry 4.0 with end-to-end supply chain management
Smart Industry 4.0 with end-to-end supply chain management
Tiny machine learning and computer vision at the edge
The problem.
Do you know where your product is, where it is going to be and in what quantities? This is the challenge that many manufacturers and logistics companies face in the management of their supply chains. As more functions are outsourced and supply chains become more complex, traditional approaches to keeping track of product movements are unable to keep pace.
Some of the main challenges of tracking goods within the supply chain using Computer Vision are:
- answering “where & when” the goods are in micro level
- volatile environment (product variability, environmental conditions)
- real time processing
- privacy-sensitive product handling
- integration with multiple systems (RFID, availability stall, access control etc)
In collaboration with:
The solution.
In this demo we will show how Irida Labs is providing real-world edge vision solutions, while addressing issues in indoor and industrial applications like enabling smart tracking for the supply chain and Industry 4.0. The detection and tacking procedures are facilitated using an EVLib component, a complete embedded vision software library developed by Irida Labs based on deep learning.
Real-time Supply Chain Management in Industry 4.0 using a network of vision sensors and AI.
The advantages.
The proposed application detects people, objects and vehicles using depth-only information, achieving remarkable levels of accuracy and robustness. Our goal is to provide an easily scalable and cost-efficient solution, that can be implemented in a wide variety of real-life scenarios.
- Low cost & low power, scalable and versatile system design
- Integrates to 3rd party systems
- Privacy preserving – no cloud processing
- Improves warehouse, logistics, supply chain management
- Extensible and re-purposable Hardware investment
- Facilitates conformation to regulations during post-COVID era
The applications.
Businesses that have a physical presence of people and objects, such as warehouses, docking areas, construction sites can benefit from accurate warehouse management solutions, real time supply-chain management and inventory monitoring, process automation and smart logistics. Warehouse and Logistics vision-based AIoT sensors provide scalable solutions to the real-world pain points of on-site space optimization, employee safety, simplification of asset management tasks as well as supply chain bottleneck identification.
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Learn more about the proposed solution including hardware and software comparisons, as well as the technical details used in this Use Case, the system architecture, hardware components and ML engine.