Weighted Constraint Satisfaction for Smart Home Automation and Optimization

Abstract

Automation of the smart home binds together services of hardware and software to provide support for its human inhabitants. The rise of web technologies offers applicable concepts and technologies for service composition that can be exploited for automated planning of the smart home, which can be further enhanced by implementation based on service oriented architecture (SOA). SOA supports loose coupling and late binding of devices, enabling a more declarative approach in defining services and simplifying home configurations. One such declarative approach is to represent and solve automated planning through constraint satisfaction problem (CSP), which has the advantage of handling larger domains of home states. But CSP uses hard constraints and thus cannot perform optimization and handle contradictory goals and partial goal fulfillment, which are practical issues smart environments will face if humans are involved. This paper extends this approach to Weighted Constraint Satisfaction Problem (WCSP). Branch and bound depth first search is used, where its lower bound is estimated by bacterial memetic algorithm (BMA) on a relaxed version of the original optimization problem. Experiments up to 16-step planning of home services demonstrate the applicability and practicality of the approach, with the inclusion of local search for trivial service combinations in BMA that produces performance enhancements. Besides, this work aims to set the groundwork for further research in the field.