No abstract

With the aid of Alibaba Cloud platform, this system builds a cloud database server, and uses short-distance wireless communication ZigBee one-to-many networking technology, RFID technology and Android development and application technology to realize mobile phone clients’ remote real-time acquisition of indoor and outdoor parameters transmitted by mobile robots, and a monitoring system that can be automatically adjusted. The mobile robot car walks indoors according to a predetermined track, and detects the greenhouse degree, light intensity, combustible gas concentration and other environmental parameters of each indoor location in real time and transmits them to the mobile APP terminal for real-time display. By comparing the indoor terminal parameters and set values, the home lighting, fan curtains, etc. can be automatically adjusted by mobile robot or manually adjusted by mobile APP. Finally, the system has been tested as a whole, and the test results show that the system has successfully achieved the expected goal, and the operation is convenient, with a certain market practical value.

In this research, a robust face recognition method based on adaptive image matching and a dictionary learning algorithm was proposed. A Fisher discriminant constraint was introduced into the dictionary learning algorithm program so that the dictionary had certain category discrimination ability. The purpose was to use this technology to reduce the influence of pollution, absence, and other factors on face recognition and improve the recognition rate. The optimization method was used to solve the loop iteration to obtain the expected specific dictionary, and the selected specific dictionary was used as the representation dictionary in adaptive sparse representation. In addition, if a specific dictionary was placed in a seed space of the original training data, the mapping matrix can be used to represent the mapping relationship between the specific dictionary and the original training sample, and the test sample could be corrected according to the mapping matrix to remove the contamination in the test sample. Moreover, the feature face method and dimension reduction method were used to process the specific dictionary and the corrected test sample, and the dimensions were reduced to 25, 50, 75, 100, 125, and 150, respectively. In this research, the recognition rate of the algorithm in 50 dimensions was lower than that of the discriminatory low-rank representation method (DLRR), and the recognition rate in other dimensions was the highest. The adaptive image matching classifier was used for classification and recognition. The experimental results showed that the proposed algorithm had a good recognition rate and good robustness against noise, pollution, and occlusion. Health condition prediction based on face recognition technology has the advantages of being noninvasive and convenient operation.

Aiming at the development of solar light monitoring system in China, and combining Zigbee and GPRS technology, a monitoring system for solar light has been designed and realized in this paper. The system is mainly composed of four parts: road lamp control unit, ZigBee module, GPRS module, and monitoring and managing software. The street light unit is applied to collect state information, ZigBee module to realize wireless assembling and gather state information to the central node, GPRS module to transmit remote state information to the monitoring and managing computer. The monitoring and managing software provides man-machine management interface finally. Due to its advantages of low cost, high efficiency and intellectualization, the system will be put into use this year as soon as possible.

With the development of the society, the improvement of people’s living standards, countless underground parking lots seem to be difficult to park and find cars. Underground parking lot was built under the thick concrete. Because the underground parking lot is built under the thick steel and cement, the GPS satellite signal can not penetrate the thick bunker, which leads to the problem that the navigation accuracy in the building is too low to be able to locate accurately. In order to solve this problem which is put forward an intelligent underground parking guidance system based on the wifi, the system install wifi routers on the underground parking lot, and mobile phones own wifi module scan wifi hotspots around the information, and then match the cloud database tagged wifi hotspots information, and get wifi hot spot on the map coordinate information. According to the mobile phone access to the location of the WIFI hotspot intensity information, the system gets to the phone’s current location information, and the coordinates of the map is updated. Fianlly, according to the system for the whole test, the test results show that the system has achieve the expected goals, and the operation is convenient, has certain market practical value.