Abstract: Embodiments of the present invention provide a computer system a computer program product, and a method that comprises, in response to receiving a request for a task to be performed, optimizing configured operational parameters based on prioritized user parameters and environmental details associated with the task; calculating a value of the task based, at least in part, the optimized configured parameters, environmental details associated with the task, and prioritized user parameters; and performing the task based on the optimized, configured parameters and calculated value.

Abstract: A method, computer system, and a computer program product for internal product composition analysis is provided. The internal product composition analysis may begin by receiving a product return identifier associated with a product and then retrieving a plurality of product data based on the received product return identifier, wherein the retrieved plurality of product data includes one or more expected features. Then one or more internal images of the product are generated and one or more internal features of the product are identified from the generated one or more internal images The identified one or more internal features may then be compared with the one or more expected features and in response to determining that the identified one or more internal features match the one or more expected features, accepting the product return.

Abstract: Embodiments of the present invention provide a computer system a computer program product, and a method that comprises, in response to receiving a request for a task to be performed, optimizing configured operational parameters based on prioritized user parameters and environmental details associated with the task; calculating a value of the task based, at least in part, the optimized configured parameters, environmental details associated with the task, and prioritized user parameters; and performing the task based on the optimized, configured parameters and calculated value.

Abstract: Product discovery is enhanced by allowing a user in a connected kitchen to share their food consumption habits with friends and trusted companies. Smart devices installed in the kitchen sense the food being prepared, such as a camera which automatically records an image of a food item, and image recognition is performed to identify the item. A cloud server has contact information for individuals associated with the user such as designated friends or social groups, and also has promotional information for available sales offers regarding food-related products. The server generates a food product recommendation based on the dish being prepared by the user and based on the sales offers, and sends a notification to the friends identifying the user, the dish and a particular sales offer. The system rewards users based on their influence, gleaned from the number of such offers that are accepted by the friends.

Abstract: Product discovery is enhanced by allowing a user in a connected kitchen to share their food consumption habits with friends and trusted companies. Smart devices installed in the kitchen sense the food being prepared, such as a camera which automatically records an image of a food item, and image recognition is performed to identify the item. A cloud server has contact information for individuals associated with the user such as designated friends or social groups, and also has promotional information for available sales offers regarding food-related products. The server generates a food product recommendation based on the dish being prepared by the user and based on the sales offers, and sends a notification to the friends identifying the user, the dish and a particular sales offer. The system rewards users based on their influence, gleaned from the number of such offers that are accepted by the friends.