Abstract: The present application relates to the use of soft nano material integrated to micro-electronics circuit to detect signals from nutritional substances and the subsequent conversion of these signals into format suitable for a trained machine learning model through pre-processing steps prior to sending to the machine learning model as well as the output format of the machine learning model and post processing in order to obtain a final determination of the quality and predicted expiration date of a nutritional substance within a probabilistic confidence level. The application encompasses a soft nano-material integrated with micro-electronics for signal capture and an analytics platform for machine learning model training, classification and prediction with a probabilistic confidence level result.

Abstract: The present application relates to the use of soft nano material integrated to micro-electronics circuit to detect signals from nutritional substances and the subsequent conversion of these signals into format suitable for a trained machine learning model through pre-processing steps prior to sending to the machine learning model as well as the output format of the machine learning model and post processing in order to obtain a final determination of the quality and predicted expiration date of a nutritional substance within a probabilistic confidence level. The application encompasses a soft nano-material integrated with micro-electronics for signal capture and an analytics platform for machine learning model training, classification and prediction with a probabilistic confidence level result.

Abstract: A data management system for processing data collected from a plurality of money services businesses servers and market exchange rate platform. The data management system comprising a communication interface communicatively coupled with said plurality of systems hosted at remote servers locations. The communication interface may be configured to receive, from said plurality of systems; data based on input search parameters and store said data in storage. The data management system may comprise an analytics computing platform operatively coupled with data storages over a communication network. The said data storages hold a dataset comprising money services business data, total amount received per dollar index data and market exchange rate data. The analytics computing platform may employ a big data processing framework to stream the dataset and a production machine learning algorithm to analyze the said dataset vis-à-vis a matrix of features to predict money services business data price movements.