Rapid 

Quality Detection 

NIRWatchdog is a quality control solution using Near-Infrared Spectroscopy to authenticate raw materials to avoid economic losses due to tampering using NIR devices, Machine Learning, Blockchain Technology, Automated Storage, and a customized smartphone application.

NIRWatchDog
 

How It Works

SnT NIR Watchdog is a product with the ability to solve real problems of clients in various industries, specifically for authentication of products’ raw materials susceptible to economically motivated tampering. The NIRWatchdog software platform combines several modules to provide the ability to identify a deviation of material from the standard in a given population. For example, a commercial package may be identified by the system as deviating from the standard range acceptable for its class and flagged for further fraud or quality control checks.

 

The system uses electromagnetic reflectance readings from a Near-Infrared (NIR) Spectrometer. The scan results are sent to the comparison algorithm which determines with a certain probability whether the scanned product could belong to the trained samples’ family. Inspection data is stored in the encrypted database on a blockchain, containing scan data, digital signature, location along with the hash value of the data.

 

The technology is based on the Raman Effect using the near-infrared spectrum response. Our software platform (NIR Watchdog) gets an input reading from a Near-Infrared (NIR) Spectrometer and builds a molecular fingerprint of the scanned product using machine learning. After the fingerprint is identified, the system identifies an indication of any suspected deviations of the inspected material from the standard. With a current measured accuracy of detection above 98%, NIRWatchdog provides a rapid, easy-to-use method for quality detection and control.

 
 

Why Choose NIRWatchdog

 

Secure Data Storage and Visualization

NIRWatchdog is the only NIR service company to provide secure, encrypted data storage stored on a blockchain.

Each spectral data is bound to the spectrometer used by a digital signature. Our blockchain technology records tag information related to the spectral data, such as hash value, signature, timestamp, and system ID. The authenticity of spectral data is essential if the testing is applied to regulatory uses, such as food inspection.

To all users, NIRWatchdog provides an interactive dashboard, providing an easy-to-use interface for data visualization.

NIRWatchdog Secure Data Storage and Visualization

Quality Control Solution

The NIRWatchdog platform combines several modules to identify a deviation of material from the standard material in a given population. The platform includes customized data analysis to identify your materials' personalized fingerprint, algorithm development, model training, testing, and prediction results to determine product deviation. We can also provide training and support for your staff throughout the process to ensure ease-of-use.

The NIRWatchdog iPhone app takes your personalized data fingerprint and provides a prediction analysis in seconds. By providing measurements of reflectance, absorbance, and intensity, you can see the fingerprint of each object in real-time and send it to our servers for prediction analysis based on our customized algorithms.

why choose NIRWatchdog New Scan
Secure Data Storage and Visualization

Data Analytics

NIRWatchdog provides in-depth data analysis customized to meet your needs. Services include but are not limited to, NIR fingerprinting your product, model training, testing, and prediction to determine product deviations and counterfeits. 

Inspection data is stored in an encrypted database using blockchain technology, containing scan data, digital signature, location along with the hash value of the data.

Proof of Concept

We currently work with a major food producer with a dedicated focus on quality control. Our system is capable of rapidly identifying problems related to package quality and content, as well as adapting to existing quality control processes. The tamper-proof and trusted process coupled with our own proprietary machine learning methods reduces the detection time by multiple orders of magnitude.

 
 

Meet The Team

Dr. Radu State

Dr. Radu State

Professor, SnT

Nino Chaganava

Nino Chaganava

Project Manager, SnT

Jorge Meira

Jorge Meira

Research Associate, SnT

Image from iOS.jpg

Andres Melendez

Research & Development, SnT

Manzing Du

Manxing Du

Technical Consultant

 

Contact Us

29 Avenue John F. Kennedy, Luxembourg, Luxembourg

info@nir-watchdog.lu

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