With the development of urbanization, the city has entered the stage of improving the quality of the stock, and the number of urban demolition has increased, resulting in the generation of construction waste and great pressure on the environment. The discharge of construction waste threatens the sustainable development of urban environment. And because large public buildings have high energy consumption and high emissions, it is urgent to establish an effective energy consumption measurement system. In the past, the calculation method for energy consumption was relatively single, which could not effectively manage energy consumption. This paper discusses how to use construction waste scientifically based on the Internet of things, and using advanced measurement technology to monitor and analyze building energy consumption is an effective way to solve this problem. Based on this, this paper constructs a building energy consumption measurement system through the Internet of things technology. By using BP linear neural network model to predict, the system effectively improves the prediction accuracy and makes it close to the actual value. The system is mainly based on the collection terminal, the centralized data terminal and the data management terminal, and then builds a communication bridge between the terminals through the Internet of things and the Internet. The response time of energy consumption monitoring and management is relatively short, and the response speed of power control management and energy consumption management analysis is relatively fast, which can effectively measure the energy consumption of buildings. In addition, this paper also makes a brief analysis of the recycling of construction waste, and puts forward the corresponding strategic analysis of resource utilization. This paper designs an effective energy consumption measurement system by introducing the Internet of things technology into the building field.