We offer sensory detection (I-Noses) to detect the presence of harmful and volatile components. In near future we will empower the detection of unwanted components based on color differenetiations with image processing capabilities installed in our edge devices
Different branches have different detection needs. Our I-Nose edge devices are adaptive and modular. Based on the sensory needs and the information, which is needed to be collected in different environments, I-Nose will be designed and built adaptable to your detection criteria. Whether you need to detect the variations in odors or air quality control or detect dangerous gases, we have a device for you.
I-Noses are coupled with image processing instrument and analytics to beside odor profile, give you the imagery information needed for structuring a comprehensive database and stablish a correlation between the odor and appearance in your production line.
Different branches have different analysis needs. I-Sense is a cloud-based AI platform designed to meet all the data analysis needs in different branches.
Whether you need to analyse the content of the grain or control the quality of the wine, you can choose amongst a variety of analysis techniques such as PCA, PLA, PLS and many others to make sure of the quality of the product and be alerted when irregularities are observed.
I-Sense is user interactive. This enables the user to upload data and notes to specific measurements and improve the detection capabilities using our AI machine learning instrument implemented in the platform. This data is also used to improve the detection capabilities in general and provide users with better quidelines to improve their production quality.
This AI powered database, stores the generated information from all I-Nose devices installed in different environments. The raw data is then available for further analysis by the solution owner and other research facilities to improve the detections accuracy.
Research facilities can purchase the raw data they are interested at in order to study the samples further