Indoor intelligent energy saving system based on Internet of Things and machine learning

Abstract

The invention discloses an indoor intelligent energy saving system based on Internet of Things and machine learning. The indoor intelligent energy saving system based on the Internet of Things disclosed by the invention comprises a control input parameter module, a main control unit of the Internet of things, a terminal node set of the Internet of things, a terminal device set, an intelligent energy saving system module and an effect feedback module. The input parameter module comprises a variety of control input parameters, comprising, but not limited to, device control events, human sensingsensors, ambient light sensing sensors, area information, planned schedules, user preferences, scene information, environmental sensors, and the like. The indoor intelligent energy saving system disclosed by the invention has the beneficial effects that: 1. energy conservation, user experience and work performance can be comprehensively optimized by the cooperative use of the Internet of Things and an intelligent algorithm; and 2. multiple input parameters are comprehensively input, so that the decision making is more comprehensive and more scientific.

Description

technical field [0001] The invention relates to the field of indoor energy saving, in particular to an indoor intelligent energy saving system based on the Internet of Things and machine learning. Background technique [0002] There are many studies on indoor energy saving. Most of the previous studies focused on improving the energy saving effect of lighting systems, and more from the perspective of energy saving and consumption reduction. In fact, the indoor energy-saving system should be a multi-objective system. As the main place for people to work, study and live indoors, people's comfort cannot be ignored blindly for the sake of energy saving. In particular, with the continuous improvement of people's living standards, people's requirements for work, study and living environments are also getting higher and higher. Therefore, in this context, on the basis of energy saving, the importance of improving user experience should also be considered, and the energy saving co...

AI Technical Summary

Problems solved by technology

[0012] 2. This type of research is still in the experimental and verification stage, and has not been applied to real-world scenarios on a large scale

[0023] 1. Simply by replacing high-efficiency LEDs, turning off the lighting in a timely manner, and reducing the brightness in a timely manner to achieve energy saving, the energy saving is relatively simple and has no intelligence;

[0024] 2. Most of the technical research focuses on the energy saving of indoor lighting systems or air conditioning systems, but the energy saving of other electrical equipment (such as computers) is not touched;

[0025] 3. The energy-saving algorithm is relatively simple. Basically, a small number of parameters and preset rules are used to judge whether to switch equipment, which cannot be applied to diverse equipment, many environmental parameters, and high individual requirements;

[0027] 5. Does not consider the difference in user requirements for environmental parameters (such as: brightness, color temperature, temperature and humidity, etc.) in the use scene, and the exploration of user experience is not deep enough

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