Accenture Global Solutions Limited

Akshay Tutika

Anshul Gupta

Bolaka Mukherjee

Vipin Anilkumar Bhasin

Ankur Garg

Jyoti Bishnoi

Meeta Lal Budhrani

Pallav Chourey

Richa Sahrawat Malik

Yogesh Kanoi

Suman Nelli

Vinivesh Raina

Systems and methods for inclusive product design are disclosed. The system obtains likeness score for product attributes for product using survey before design phase of product, from user(s), and determines impact and relative contribution of each product attribute, for user, to inclusivity score, using multi-level machine learning models. The system segregates product attributes and inclusivity score at persona level, and determines feature importance score of each feature in product attributes for each user. System calculates risk score for each user indicating sensibility towards product designer choices, and provides what-if analysis capabilities to product designer for analyzing, based on risk score, risk of each user with sensibility towards product designer choices and receives multisensory review from user. The system computes overall score by combining feature importance and inclusivity scores, facial coding, voice tonality, and haptics feedback, to granular level and outputs iteratively enriched survey data for inclusive designing of products.

Inclusive product design

Examples for the baggage weight prediction system are provided. The system may create a baggage prediction model in response to a carrier baggage weight prediction requirement requesting a total baggage weight to be carried in a future transportation operation by a carrier. The baggage prediction model may be used to determine a predicted baggage to be carried by a plurality of future passengers associated with a future transportation operation. The system may determine a predicted weight for the predicted baggage. The system may sort the predicted baggage into checked baggage and a carry-on baggage. The system may determine a carry-on baggage weight associated with the carry-on baggage based on the baggage prediction model. The system may determine a baggage weight ratio associated with the predicted baggage. The system may generate a baggage prediction result for performing a baggage management action.

Baggage weight prediction

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Hyderabad Telangana, India

Akshay Tutika