Abstract: A system for centralized planning and analytics for greenhouse growing of hydroponic produce, the system comprising: at least one greenhouse; an imaging system; a climate module; a forecasting system; a storage medium; a processor which comprises at least a machine learning algorithm which improves the accuracy and the yield forecast; and a network which provides a communication pathway for information to move between at least two of the group consisting of: the greenhouse, the imaging system, the climate module, the storage medium and the processor; wherein the forecasting system generates crop analytics from the imaging system; generates climate trends from the climate module disposed in each the at least one greenhouse; and uses a machine learning algorithm to determine yield forecast of the hydroponic produce.

Abstract: Artificial intelligence based systems and methods for analyzing user-specific data to predict user-specific skin or hair conditions. User-specific data of a user is received at a scalp and hair analysis application and defines a scalp or hair region of the user including last wash data of the user and at least one other factor of the user. An artificial intelligence based learning model, trained with training data regarding scalp and hair regions of respective individuals, analyzes the user-specific data to generate a scalp or hair prediction value corresponding to the scalp or hair region of the user. The application generates, based on the scalp or hair prediction value, a user-specific treatment designed to address at least one feature based on the scalp or hair prediction value of the user's scalp or hair region.

Abstract: Artificial intelligence-based systems and methods are described for interacting with individuals via a web environment. A provisioning server is configured to receive a request from a web browser, executing on a client device, for a predefined imaging code stored in a memory of the provisioning server. The provisioning server responds to the request by transferring the predefined imaging code to the web browser. The predefined imaging code is configured to be executed by the client device to load, into a memory of the client device, one or more images of an individual; and determine, based on image analysis of the one or more images of the individual, one or more personal attributes of the individual.

Abstract: Artificial intelligence-based systems and methods are described for interacting with individuals via a web environment. A provisioning server is configured to receive a request from a web browser, executing on a client device, for a predefined imaging code stored in a memory of the provisioning server. The provisioning server responds to the request by transferring the predefined imaging code to the web browser. The predefined imaging code is configured to be executed by the client device to load, into a memory of the client device, one or more images of an individual; and determine, based on image analysis of the one or more images of the individual, one or more personal attributes of the individual.

Abstract: Artificial intelligence based systems and methods are described for interacting with individuals via a web environment. A provisioning server is configured to receive a request from a web browser, executing on a client device, for a predefined imaging code stored in a memory of the provisioning server. The provisioning server responds to the request by transferring the predefined imaging code to the web browser. The predefined imaging code is configured to be executed by the client device to render an interactive graphical user interface (GUI) within the web browser on a display of the client device; load, into a memory of the client device, one or more images of an individual; determine, based on image analysis of the one or more images of the individual, one or more personal attributes of the individual; and, render the one or more personal attributes of the individual within the interactive GUI.