Abstract:

To addressing the critical issues faced by traditional heating systems, such as uneven temperature distribution, significant energy wastage, and inefficiencies associated with manual control, an advanced IoT-based intelligent monitoring system utilizing NB-IoT(Narrow Band Internet of Things) technology is designed.The primary objective is to enhance the efficiency, reliability, and user satisfaction of community heating networks through modern technological integration. The proposed system integrates contemporary communication technologies, sensor data acquisition, cloud-based AI analysis, and edge computing. It consists of portable temperature measurement nodes, NB-IoT communication modules, an AI co-processor for local intelligence, and a cloud server for centralized management. Specifically, up to 16 temperature-measuring nodes and two base stations are deployed within the network. These terminal nodes collect indoor heating temperatures alongside user-defined settings, transmitting gathered data via NB-IoT to a cloud server where it undergoes intelligent processing facilitated by an edge gateway. This processed data is then visually displayed on a user interface,enabling historical reference, anomaly detection, and predictive analysis for temperature patterns. Testing results demonstrate substantial improvements in system performance, including a notable reduction in power  consumption, and the overall system current in sleep mode is≤8μA,which extends battery life expectancy beyond two years. The system significantly enhances user satisfaction by providing more consistent and comfortable indoor temperatures. With its proven capability to reduce energy waste and improve operational efficiencies, the system not only promises considerable economic benefits but also establishes itself as an effective solution to the inherent limitations of conventional heating systems. Thus, this work contributes to the advancement of smart community infrastructure, promoting sustainable and efficient heating solutions.

Key words: