An AmI-based and privacy-preserving shopping mall model

Nowadays, large shopping malls provide tools to help and boost customers to buy products. Some of these tools melt down digital operations with physical ones executed by customers into blended commerce experiences. On the other hand, ambient intelligence (AmI) represents a paradigm focused on equipping physical environments to define ergonomic spaces for people interacting with computer-based localized services which are ubiquitously accessible. In this context, we propose a framework based on cellular automata (CA), a very well known formal computational model, suitable to abstract services deployed into an AmI-based environment preserving certain privacy levels of shoppers’ information. CA-based algorithms are advantageous because they are distributed, scalable, on-line and require low costs to be deployed. This work proposes a recent application of CA, namely Cellular ANTomata, to implement a service by which shoppers are guided to find the suitable offerings for items in their shopping lists. A further result provided by this paper is the instantiation of a protocol for privacy-preserving shopping experience in the shopping mall.