Introduction Wireless Sensor Networks (WSNs) are "intelligent" autonomous monitoring and control network systems composed of a large number of ubiquitous, communication- and computing-capable tiny sensor nodes densely distributed in unattended monitoring areas, capable of autonomously completing designated tasks according to the environment. If the Internet has changed the way people communicate with each other, then WSNs will merge the logical information world with the real physical world, changing the way humans interact with nature. For this reason, in 2003, MIT Technology Review listed it as one of the top ten emerging technologies that will change the world in its report predicting future technological developments. Bluetooth is a short-range wireless communication technology specification. Because Bluetooth operates in the 2.4 GHz ISM (industrial, scientific, and medical) band; it can transmit voice and data simultaneously; and it has good anti-interference capabilities and low power consumption, building Bluetooth sensor networks composed of fixed sensor nodes using Bluetooth technology is an emerging research direction in the field of wireless sensors, enabling information collection, processing, and transmission in certain special situations. This paper introduces the construction of a Bluetooth sensor network for square environmental monitoring and the design of sensor nodes, and studies the node localization and power supply issues of the Bluetooth sensor network. Finally, it discusses the existing problems and development directions in the WSN field. 1 Bluetooth Sensor Network Construction The entire Bluetooth sensor network consists of several Bluetooth sensor nodes and a monitoring host. The wireless sensor nodes are distributed around the square to be monitored, performing data acquisition, preprocessing, and transmission. The monitoring host is placed inside a smart car and communicates with the sensor nodes via a Bluetooth module. 1.1 Bluetooth Sensor Network Model To input signals to the terminal, Bluetooth is used instead of wired, infrared, or optical signal transmission because it is best suited for short-range, low-power wireless communication. A sensor network built using Bluetooth is called a Bluetooth sensor network. To provide a more intuitive explanation of the Bluetooth sensor network, a Bluetooth sensor network model is constructed. The Bluetooth sensor network model is based on the principle of proximity networking; two Bluetooth sensors that are close enough to each other can spontaneously establish a communication link via the Bluetooth module. In Bluetooth networking, up to 256 Bluetooth devices can connect to form a piconet. One master node and seven slave nodes are active, while the others are idle. The master node controls the bandwidth of the asynchronous connectionless (ACL) link and determines how much bandwidth each node in the piconet can use and the symmetry of the connection. Slave nodes can only send data when selected; that is, slave nodes must be polled before transmitting data. Piconet networks can overlap and intersect, and slave devices can share bandwidth. A network composed of multiple overlapping piconet networks is called a seatternet. The sensor network used for square environmental monitoring consists of piconet networks composed of sensor nodes pre-placed around the square, and these piconet networks form a seatternet. Its network communication architecture is shown in Figure 1. Nodes have sensing, signal processing, and wireless communication functions; they are both packet initiators and packet forwarders. Data is sent to the monitoring system through network self-organization and multi-hop routing. 1.2 Bluetooth Sensor Network Node Localization Node localization refers to the mechanism of determining the positions of other nodes in a deployment area based on a limited number of known nodes, thus establishing spatial relationships between sensor nodes. In most cases, the data acquired by the sensor network is only meaningful when combined with location information. Furthermore, research on Bluetooth sensor network protocols also utilizes node location information. At the network layer, because Bluetooth sensor network nodes lack global identifiers, a routing algorithm based on node location information was designed. At the application layer, based on node locations, the Bluetooth sensor network system can intelligently select specific nodes to complete tasks, thereby reducing the overall system's energy consumption and increasing its lifespan. Since the positions of each sensor node in the designed Bluetooth sensor network system are fixed, a distance-based node localization mechanism can be adopted. The node position is calculated using maximum likelihood estimation by measuring the point-to-point distance between nodes. The distance-based localization mechanism requires that the two nodes have the ability to measure the distance between them. TDOA (time difference on arrival) ranging technology was adopted. Ultrasonic transceivers and Bluetooth transceivers were installed on the nodes. During ranging, at the transmitting end, two transceivers simultaneously transmit signals. Utilizing the significant difference in the propagation speeds of sound waves and electromagnetic waves in air, at the receiving end, the difference in arrival times of the two different signals is recorded. Based on the known signal propagation speeds, time is directly converted into distance. This technology can achieve ranging accuracy down to the centimeter level, but it is limited by the finite propagation distance of ultrasonic waves and the influence of non-line-of-sight (NLOS) issues on the propagation of ultrasonic signals. 2. Sensor Node Design The design of sensor nodes mainly includes: hardware design, software design, and power supply design. 2.1 Overall Sensor Node Design In different applications, sensor node designs vary, but their basic structure is the same. Based on specific needs, the designed sensor node mainly consists of the following subsystems: a data processing subsystem, a data acquisition subsystem, a wireless communication subsystem, and a power supply subsystem. A schematic diagram of the node structure is shown in Figure 2. 2.2 Sensor Node Hardware Design The sensor node mainly consists of an ultra-low-power processor, various sensors, and their auxiliary circuits. A schematic diagram of the node is shown in Figure 3. 2.3 Power Supply Issues Power supply is a critical issue in WSNs. Only by providing a long-term, effective energy source can sensor networks reduce maintenance and operating costs and further demonstrate their significant advantages. To maximize energy conservation, the microcontroller in the node design executes tasks at the fastest speed and enters energy-saving mode whenever possible. In energy-saving mode, the power management circuit cuts off the power supply to all devices except the microcontroller, Bluetooth module, and hardware watchdog. At this time, only the hardware watchdog, the microcontroller's serial interrupt logic, and the Bluetooth module consume power, maximizing energy savings. After the node starts up and completes necessary tasks, including initializing the Bluetooth device and obtaining the local address, it enters energy-saving mode. Once in energy-saving mode, if the monitoring center needs to access the node, it wakes up the node's microcontroller via the Bluetooth module. 2.3.1 Power Management Dynamic power management is an effective design method for reducing system energy consumption in sensor networks. Dynamic power management is an effective way to reduce system power consumption without affecting system performance. The basic idea is that devices within the sensor node are turned off when not needed and woken up when needed. This allows the sensor to enter the appropriate low-power mode in a timely manner, reducing overall energy consumption. The fundamental premise for the applicability of dynamic power management technology is that system components have varying workloads during their operating hours, a situation present in most systems. Another premise is the ability to predict, to a certain extent, the fluctuations in the system and component workloads. This allows for the possibility of switching energy-consuming states, and ensures that the system does not consume excessive energy within the timeframe of observed and predicted workload. In sensor networks, the various modules constituting sensor nodes have different power states; therefore, dynamic power management is a suitable approach. In a dynamic power management system, the operating states of different components must dynamically adapt to varying performance requirements. Only in this way can energy wasted during idle time or by unused components be minimized. Determining the timing of power management implementation requires a dynamic prediction method, using historical workload data to predict upcoming workloads and decide whether to switch operating states and when to wake up. 2.3.2 Energy Consumption Reduction Measures 1) Employing new technologies such as system-on-chip (SoC) technology, MEMS technology, and application-specific integrated circuits can significantly reduce the number of sensor network components and thus reduce energy consumption; 2) Using sensor data fusion technology can reduce network communication volume, lower data redundancy, and improve energy efficiency; 3) Reducing transmission errors can also reduce energy consumption. 2.4 Sensor Node Software Design In the network, each node has a fixed address (determined by the Bluetooth module address). The sensor node connected to the monitoring host is a special node that communicates with the Bluetooth module and the monitoring host via a serial interface. Data transmission uses a master-slave configuration. The node connected to the monitoring host acts as the master, controlling the communication timing within the network; other nodes act as slaves and can be addressed by the master. The sensor node software design is divided into two parts: master node software design and slave node software design. The master node primarily collects data from each slave node and then analyzes and processes the data; the slave nodes primarily collect and preprocess raw data from various sensors. 2.4.1 Master Node Program Design In the master node, the monitoring host and the host controller (Bluetooth module) exchange information via Bluetooth host controller interface (HCI) packets. After executing the monitoring host's instructions, the host controller generates result information and sends this information to the monitoring host through corresponding event packets. In a Bluetooth sensor network, the simplest ACL data communication process between the Bluetooth module on the master node and the Bluetooth modules of other nodes has five steps: Bluetooth module initialization, query, connection establishment, data communication, and disconnection. The flowchart of the master node program is shown in Figure 4. Based on the processed data, real-time information about the square environment can be obtained, and corresponding measures can be taken in a timely manner for emergencies. Furthermore, the lighting brightness and duration can be set according to the brightness of the square, providing both early warning and energy saving. 2.4.2 Slave Node Program Design The slave node program mainly collects data from various sensors, processes it initially, and then transmits it to the master node. Its program flowchart is shown in Figure 5. 3 Conclusion The entire network adopts a master-slave station structure, with the master station uniformly controlling the communication timing within the network. The nodes are based on the low-power ATmega128L microcontroller and use a Bluetooth module for communication. On the software side, serial port interrupts are used for receiving and sending data. The nodes are battery-powered, and by utilizing the microcontroller's energy-saving mode, energy conservation can be maximized, extending the node's lifespan. Experiments show that WSNs established using this mode are stable, reliable, and have high communication efficiency.