Recently, all-electrified houses have constructed and some tasks are being carried out to monitor energy consumption patterns. The energy monitoring includes various elements such as temperature, pressure, water flow, CO2, and electricity. In this monitoring, electricity consumption is one of the essential factors because the performance and energy saving levels are described by this physical quantity. This quantity depends on materials, structure, operation of the house, which operation means consumer's life style and usage patterns of home appliances furthermore. Firstly, this paper shows a control simulation method which were developed a few years ago. And some different methods are proposed considering flexible experimental condition.

Due to advances in machine intelligence and increased demands for autonomous machines, the complexity of the underlying software platform is increasing at a rapid pace, overwhelming the developers with implementation details. We attempt to ease the burden that falls onto the developers by creating a graphical programming framework we named Splash. Splash is designed to provide an effective programming abstraction for autonomous machines that require stream processing. It also enables programmers to specify genuine, end-to-end timing constraints, which the Splash framework automatically monitors for violation. By utilizing the timing constraints, Splash provides three key language semantics: timing semantics, in-order delivery semantics, and rate-controlled data-driven stream processing semantics. These three semantics together collectively serve as a conceptual tool that can hide low-level details from programmers, allowing developers to focus on the main logic of their applications. In this paper, we introduce the three-language semantics in detail and explain their function in association with Splash’s language constructs. Furthermore, we present the internal workings of the Splash programming framework and validate its effectiveness via a lane keeping assist system.