Training models for prediction and monitoring using internet of things data collection

Abstract

Systems and methods for transaction platforms include various systems interacting with each other and transacting in various ways. A method for configuring and launching a marketplace includes: identifying, by a processing system having one or more processors, an opportunity to facilitate configuration of a new marketplace; receiving marketplace opportunity data, wherein the marketplace opportunity data includes information related to a set of assets of one or more types; determining configuration parameters to be implemented in the new marketplace; determining the feasibility of implementing the configuration parameters in the new marketplace; determining data resources to support the new marketplace; determining an architecture of the new marketplace; determining the configuration of the data resources in a data model for the marketplace; configuring a marketplace object; connecting selected data resources to populate the marketplace object; and launching the new marketplace.

What is claimed is: 
     
         1 . A system for training models and monitoring, the system comprising:
 a machine learning system that trains a set of machine-learned models to generate a prediction, wherein the machine learning system trains the set of machine-learned models using training data including market features and outcomes;   a neural network system that generates the prediction based on the machine-learned models in response to a prediction request; and   a lending platform including an Internet of Things data collection system for monitoring at least one of a set of assets and a set of collateral.   
     
     
         2 . The system of  claim 1 , wherein the prediction is a prediction for a parameter of demand in a forward market for an asset. 
     
     
         3 . The system of  claim 1 , wherein the prediction is a prediction for a parameter of supply in a forward market for an asset. 
     
     
         4 . The system of  claim 1 , wherein the prediction is a prediction of a set of terms and/or conditions for a smart contract. 
     
     
         5 . The system of  claim 1 , wherein the prediction is based at least in part on crowdsourced data. 
     
     
         6 . The system of  claim 1 , wherein the prediction is based at least in part on behavioral data collected from a set of IoT systems monitoring a set of entities in a set of environments. 
     
     
         7 . The system of  claim 1 , wherein the neural network system includes a recurrent neural network. 
     
     
         8 . The system of  claim 1 , wherein the neural network system includes a convolutional neural network. 
     
     
         9 . The system of  claim 1 , wherein the neural network system includes a combination of a recurrent neural network and a convolutional neural network. 
     
     
         10 . The system of  claim 6 , wherein the set of Internet of Things systems includes a set of smart home Internet of Things devices. 
     
     
         11 . The system of  claim 6 , wherein the set of Internet of Things systems includes a set of workplace Internet of Things devices. 
     
     
         12 . The system of  claim 6 , wherein the set of Internet of Things systems includes a set of Internet of Things device to monitor a set of consumer goods stores. 
     
     
         13 . The system of  claim 1 , further comprising a security monitoring system for monitoring assets and/or collateral based on the data collected by the Internet of Things data collection platform. 
     
     
         14 . The system of  claim 13 , wherein the security monitoring system uses machine-learned models to determine a condition or value of items based on data collected by the Internet of Things data collection platform. 
     
     
         15 . The system of  claim 14 , wherein the data collected by the Internet of Things data collection platform is image data, sensor data, or location data. 
     
     
         16 . The system of  claim 13 , further comprising a management system that enables access to information from the Internet of Things data collection system and the security monitoring system. 
     
     
         17 . The system of  claim 1 , wherein the set of machine-learned models employ a convolutional neural network, a recurrent neural network, a feed forward neural network, a long-term/short-term memory (LTSM) neural network, a self-organizing neural network, and hybrids and combinations of the foregoing. 
     
     
         18 . A method, comprising:
 training a set of machine-learned models to generate a prediction, wherein training the set of machine-learned models uses training data including market features and outcomes;   generate the prediction with a neural network based on the machine-learned models in response to a prediction request; and   monitoring at least one of a set of assets and a set of collateral in a lending platform using an Internet of Things data collection system.   
     
     
         19 . The method of  claim 18 , wherein the prediction is a prediction for a parameter of demand in a forward market for an asset. 
     
     
         20 . The method of  claim 18 , wherein the prediction is a prediction for a parameter of supply in a forward market for an asset. 
     
     
         21 . The method of  claim 18 , wherein the prediction is a prediction of a set of terms and/or conditions for a smart contract. 
     
     
         22 . The method of  claim 18 , wherein the prediction is based at least in part on crowdsourced data. 
     
     
         23 . The method of  claim 18 , wherein the prediction is based at least in part on behavioral data collected from a set of IoT systems monitoring a set of entities in a set of environments. 
     
     
         24 . The method of  claim 18 , wherein the neural network system includes a recurrent neural network. 
     
     
         25 . The method of  claim 18 , wherein the neural network system includes a convolutional neural network. 
     
     
         26 . The method of  claim 18 , wherein the neural network system includes a combination of a recurrent neural network and a convolutional neural network. 
     
     
         27 . The method of  claim 23 , wherein the set of Internet of Things systems includes at least one of a set of smart home Internet of Things devices, a set of workplace Internet of Things devices, or a set of Internet of Things devices to monitor a set of consumer goods stores. 
     
     
         28 . The method of  claim 18 , further comprising a security monitoring system for monitoring assets and/or collateral based on the data collected by the Internet of Things data collection platform. 
     
     
         29 . The method of  claim 28 , wherein the security monitoring system uses machine-learned models to determine a condition or value of items based on data collected by the Internet of Things data collection platform. 
     
     
         30 . The method of  claim 18 , wherein the set of machine-learned models employ a convolutional neural network, a recurrent neural network, a feed forward neural network, a long-term/short-term memory (LTSM) neural network, a self-organizing neural network, and hybrids and combinations of the foregoing.