International Business Machines Corporation

Vinayak Sastri

Kuntal Dey

Seema Nagar

Meenal Kapoor

Arvind Agarwal

Abhijit Mishra

Jitendra Singh

Mukul Tewari

Joydeep Mondal

Methods, computer program products, and systems are presented. The methods include, for instance: training of a machine learning model for predicting a rating in certain content rating systems based on training data. The machine learning model includes a plurality of maturity classifiers corresponding to individual features of the previously rated contents. An input content is obtained and features of the input content are extracted by use of respective content analysis tools and subsequently classified by the maturity classifiers of the machine learning model.

Dynamic content rating assistant

A computer-implemented method for effective agriculture and environment monitoring. The method may comprise measuring a desired variable over an area of interest using a remote inspection platform according to an inspection plan, predicting an occlusion of the remote inspection platform, and in response to the predicted occlusion, determining whether to invoke a local inspection platform to complete the inspection plan. The occlusion in some embodiments interrupts the inspection plan for the remote inspection platform.

Effective agriculture and environment monitoring

Providing code offerings inside code is provided. Intent of an under-developed code within a programming environment is identified by analyzing program documentation and program code corresponding to the under-developed code. The identified intent is published as a request for bids on a network. A ranked list of software codes returned against the request for bids is provided within the programming environment. Each software code in the ranked list of software codes, along with its respective proof that includes library, documentation, and code snippet, is compared with the identified intent for relevance and sorted based on monetary value of its corresponding bid.

Providing code offerings inside code

An example operation may include one or more of receiving motor vehicle data related to a motor vehicle from a sensor, retrieving a smart contract, related to the motor vehicle data, stored in a blockchain, performing a validation of the motor vehicle data based on validation standards stored in the smart contract, in response to the validation standards not being satisfied, identifying a required corrective action to the motor vehicle, transmitting a request for the corrective action to be performed to one or more registered entities, receiving a confirmation that the corrective action is complete, creating a blockchain transaction including the confirmation, and storing the blockchain transaction in the blockchain.

Validation of vehicle data via blockchain

Methods, systems and computer program products for augmenting a programming environment for developing software code using an automated dialog system are provided herein. A computer-implemented method includes monitoring actions taken in the programming environment, determining intent of the actions taken, and generating a natural language dialog in a graphical user interface of the automated dialog system. The natural language dialog comprises suggested additional actions to be taken based at least in part on the determined intent, where the suggested additional actions affect code files in the programming environment. The computer-implemented method also includes providing, in the graphical user interface, user-activatable interface features for selecting respective ones of the suggested additional actions, and modifying one or more of the code files in the programming environment in accordance with a given suggested additional action, responsive to detecting selection of a given user-activatable interface feature corresponding to the given suggested additional action.

Programming environment augment with automated dialog system assistance

Methods, systems, and computer program products for dynamically designing street-parking policies for events are provided herein. A computer-implemented method includes generating a parking map for each of one or more events that occurred within a specified geographic area; generating, for each of the parking maps, one or more traffic condition maps; generating, for each of the one or more events, based on (i) each parking map and (ii) its associated traffic condition map, an impact map for the corresponding event; adjusting, for a subsequent event within the specified geographic area, one or more street-parking policies based on the impact on parking suitability and street usability represented by the generated impact maps, and outputting the one or more adjusted street-parking policies.

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Bengaluru, India

Vinayak Sastri