This work describes an approach to sinergistically exploit Ambient Intelligence, Smartphones of last generation and Genetic Computation in order to support innovative Blended Commerce scenarios. The paper proposes both a framework for AmI-based Blended Commerce and an instantiation of this framework to implement a scenario where a Shopping Mall is presented as an intelligent environment in which customers use the NFC capabilities of their smartphones in order to manage e-coupons that are produced, suggested (also in a context-aware way) and consumed by the same environment. In this scenario, the main function of the intelligent environment is supporting customers to define shopping plans that minimize their total costs by looking for best prices and most convenient discounts for the needed products. The paper proposes a genetic approach to find sub-optimal solutions for the shopping plan problem that is not trivial given that the final cost for a single product of a plan is dependent by the previous purchases because, in a coupon world, every purchase could generate a discount for next purchases. © 2013 IEEE.
A genetic approach to plan shopping in the AmI-based Blended Commerce
GAETA, Matteo;LOIA, Vincenzo;ORCIUOLI, Francesco;
2013-01-01
Abstract
This work describes an approach to sinergistically exploit Ambient Intelligence, Smartphones of last generation and Genetic Computation in order to support innovative Blended Commerce scenarios. The paper proposes both a framework for AmI-based Blended Commerce and an instantiation of this framework to implement a scenario where a Shopping Mall is presented as an intelligent environment in which customers use the NFC capabilities of their smartphones in order to manage e-coupons that are produced, suggested (also in a context-aware way) and consumed by the same environment. In this scenario, the main function of the intelligent environment is supporting customers to define shopping plans that minimize their total costs by looking for best prices and most convenient discounts for the needed products. The paper proposes a genetic approach to find sub-optimal solutions for the shopping plan problem that is not trivial given that the final cost for a single product of a plan is dependent by the previous purchases because, in a coupon world, every purchase could generate a discount for next purchases. © 2013 IEEE.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
