By 2050, a staggering 70% of the world’s population is projected to live and work in cities, and two-thirds of global primary energy consumption is attributed to cities, leading to 71% of global direct energy-related greenhouse gas emissions. Smart cities will consist of sustainable infrastructures with buildings as major constituents. Buildings’ energy consumption contributes to more than 70% of electricity usages, with people spending more than 90% of their time in buildings nowadays.

The objective of this project is to improve the performance of autonomous systems in dynamic environments by integrating perception, planning paradigms, learning, and databases. For the next generation of autonomous systems to be truly effective in terms of tangible performance improvements (e.g., long-term operations, complex and rapidly changing environments), a new level of intelligence must be attained.

Abstract: Generally, a cyber-physical-system (CPS) is one that combines computational and physical entities in a unified design effort. The design of CPSs needs good understanding of both subsystems, as small changes in the physical subsystem (PS) or the cyber subsystem (CS) may have significant consequences with respect to the overall system performance.