Control tower and enterprise management platform with a machine learning/artificial intelligence managing sensor and the camera feeds into digital twin

A value chain system that provides recommendations for designing a logistics system comprising:

• a machine learning system, implemented by at least one processor, that trains a first machine-learned model that outputs a logistics design recommendation given a respective set of input features relating to a specific respective logistics system, wherein the machine learning system trains the first machine-learned model based, at least in part, on a first training data set that includes features of logistics systems and corresponding outcomes;
• an artificial intelligence system, implemented by at least one processor, that receives a first request for a first logistics system design and determines a first logistics system design recommendation based on the first machine-learned model and a set of features included in the first request;
• and
• a digital twin system, implemented by at least one processor, configured to:
• generate a logistics environment digital twin of a logistics environment that incorporates the first logistics system design recommendation and one or more physical asset digital twins of physical assets;
• simulate a first logistics operation performance based on the logistics environment digital twin and the one or more physical asset digital twins to generate a simulation result that includes at least one simulated outcome corresponding to the first logistics system design recommendation;
• provide the simulation result of the first logistics operations performance simulation to the machine learning system to retrain the first machine-learned model, wherein the retraining results in a second machine-learned model;
• issue a logistics system design request to the artificial intelligence system for a second logistics system design recommendation based on a result of the first logistics operations performance simulation and the second machine-learned model;
• and
• update the logistics environment digital twin based on the second logistics system design recommendation,
• wherein the retraining includes training the second machine-learned model based on the first training data set and the result of the first logistics operations performance simulation.