Wa Si

Energy saving system for office lighting by using PSO and ZigBee network

In order to reduce the amount of wasted energy in office lighting and provide a major contribution to lowering overall energy consumption, we are developing a new energy saving system for office lighting by using adjustable lamp, ZigBee Wireless Sensor Network (WSN) and Particle Swarm Optimization (PSO).In this paper we make a prototype system which consists of one ZigBee control module, four fluorescent lamps with dimming capacity and three illumination sensors.The illumination sensors collect and send the data to the control module. After the PSO (Particle Swarm Optimization) process, the module finally sets the power of the lamps according to the PSO result. After real experiments in both sunny day and cloudy dayin a small-size office, it was proved that the system can successfully control the lights, and save considerable energy.

UHF-Band Wireless Power Transfer System for Structural Health Monitoring Sensor Network

For detecting and measuring health conditions of bridges, wireless sensor networks are used in these days. However, battery life is critically restricting the application and maintenance cost of sensor network systems. To extend life time, a wireless power transfer system at UHF band is introduced to supply the current wireless sensor network. This power transfer system is based on electric wave at 950 MHz. This power transfer system is redesigned for tiny power transmission, including a combination of a rectenna and a Cockcroft-Walton boost converter, battery board, and a control board. Also, current wireless sensor network is redesigned for power transfer system. The working flow of sensor network is modified to bottom-to-top to save power of sensor modules which are the power bottleneck of this sensor system. As a result, the system is able to support a sensor module continuously with received power of −14 dBmW, when the transmitting antenna is 30 dBmW at 10 meters distance.

Fast Road Detection Based on a Dual-Stage Structure

Road detection is an important research subject in autonomous driving. Both accuracy and efficiency are very important for road detection used in autonomous driving systems. However, these two properties are usually contradictory under certain calculation resources. In this paper, we make a good compromise between accuracy and efficiency by proposing a dual-stage detecting strategy, which consists of a fast Hough transform based road detection method and a reliable vanishing point based method. A dynamic region of interest (ROI) is proposed as a connector of the two stages. Experiments prove that our method can achieve good performance on both accuracy and efficiency.

Real-time Daylight Modeling Method for Lighting Systems Based on RBFNN

Daylight harvesting has great potential of energy saving by utilizing daylight in buildings, and the accuracy of daylight data is essential to realize daylight harvesting in lighting control systems. This paper proposes a modified RBFNN structure for daylight modeling and presents a Real-time Daylight Modeling (RTDM) method, which needs only a few illumination sensors for real-time modeling of daylight. The method uses real-time sensor data to regulate a pre-stored RBFNN (which represents the relationship between position and daylight illuminance in one scenario of daylight) to calculate real-time daylight illuminance inside the room. Simulations in a middle-sized office model show that: 1) RTDM can realize real-time daylight modeling with higher accuracy compared with existing modeling methods; 2) lighting control system using RTDM can save considerable energy by daylight harvesting.