In order to improve the hardware configuration and interaction mode of the fish tank system and realize the diversification of client functions, the purpose of real-time remote monitoring and management is achieved. A set of IoT intelligent fish tank system composed of sensor unit, signal processing unit and wireless transmission unit was designed. The system improves the algorithm of the data collected by the sensor, and proposes an improved first-order lag average filtering algorithm. The system uses composite collection information, intelligent processing, chart data analysis and other methods to transmit the processed data to the cloud server through the WIFI communication module. An APP is designed on the remote monitoring and control end, and a visual data interface of the smart fish tank is made, and the user can modify the environmental parameters conducive to the biological survival inside the fish tank through the APP, it brings great convenience to the family fish tank, and the test shows that the system network is stable and fast in response, and the overall purpose of the intelligent fish tank system is achieved.

COVID-19 infection was found in Wuhan area in early 2020. Because of the Data backlog in the initial period of Hubei province, it was not conducive to accurate establishment of the model. This article selected the number of diagnosed people in 40 districts and counties of Chongqing City near Hubei province for analysis and modeling. And the prediction model is divided into three stages. The first stage is the initial stage of prevention and control, and the virus transmission shows an exponential model growth. The second stage is the development period of prevention and control, the virus transmission shows a fluctuating state. In the third stage, which is in the mature stage of prevention and control, the virus spreads as a linear function. At the same time, the data curve of three stages and the reasons for its formation are analyzed. The laws revealed by this model have a certain theoretical basis for the prevention and control of new infectious diseases such as coronary pneumonia, which will have a certain guiding effect on the prevention and control of viruses in newly discovered countries and regions of the epidemic.

In order to solve the problems related to the management of students’ bedtime in vocational colleges and improve the efficiency of students’ bedtime management, an intelligent bed for students’ bedtime management is designed, which is composed of bed and sensor unit, signal processing unit, and ZigBee transmission unit. The algorithm of the collected pressure sensor data is improved, and an improved amplitude limiting lag average filtering algorithm is proposed. The management system uses the methods of composite collection of information, intelligent processing, big data analysis, etc. to upload the data to the cloud server, through the mobile phone app and other terminals to timely grasp the sleeping situation of students at night. The experiment shows that the system improves the efficiency of students’ bedtime management by 10%.

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Synthetic Aperture Radar (SAR) is an active remote sensing system which can be installed on aircraft, satellite and other carriers with the advantages of all day and night and all-weather ability. It is the important problem that how to deal with SAR and extract information reasonably and efficiently. Particularly SAR image geometric correction is the bottleneck to impede the application of SAR. In this paper we introduces image registration and the Susan algorithm knowledge firstly, then introduces the process of SAR image registration based on Susan algorithm and finally presents experimental results of SAR image registration. The Experiment shows that this method is effective and applicable, no matter from calculating the time or from the calculation accuracy. INTRODUCTONSynthetic Aperture Radar (SAR), which has the characteristic of all-weather, day/night and long range, can enhance radar's information acquisition capability, especially the battlefield awareness ability, and has great value in both civilian and military applications. Satellite SAR has aptotic earth-circling period, and can cover wide ground area. And with its development, satellite SAR images are widely used in cartography, land use, damage assessment, geognosy, hydrology, environmental monitoring, ocean, glacier, target detection, etc. The research on SAR image is becoming more and more deeply. SAR image registration is a necessary step of SAR image processing. It is essential for the fusion between SAR image and optical image, SAR image detection and so on.This paper does work based on these states. Firstly, the paper introduces image registration and the Susan algorithm knowledge, then introduces the process of SAR image registration based on Susan algorithm and finally presents experimental results of SAR image registration. The Experiment shows that this method is effective and applicable, no matter from the calculation time or from the calculation accuracy. IMAGE REGISTRATIONAt present, image registration method can be roughly divided into three kinds [1,2] : one kind is based on image characteristics registration, this method extracts characteristics from image firstly, and then establish image matching * cb_wang@126.com, phone 13609837896, fax 86-024-89713901 Downloaded From: http://proceedings.spiedigitallibrary.org/ on 06/25/2016 Terms of Use: http://spiedigitallibrary.org/ss/TermsOfUse.aspx mapping mode through these characteristics matching relation. Another kind is based on image frequency domain registration. In this method, two image registration computing is conversed from space domain to frequency domain by Fourier transform. The last kind is based on image gray information registration and widely used in different kinds of image registration. This method uses image grey statistics information as registration measure.If you need extract location information from SAR image or undertake comprehensive analysis on multi-temporal and multi-source information, we must carry on the high-precision geometric correction. Synthetic aper...