Most metropolitan cities have seen a rapid increase in automobile population in the last decade. Due to this, finding a place to park a vehicle has become rather hectic and time consuming. This paper, Smart parking system with IoT involving disciplined parking mechanism, aims to reduce the time taken to find a parking spot for your automobile. This will also reduce the stress on the driver and will help in conserving fuel. It uses a web application to get real time sensor data on any screen. This reduces the time taken to park the vehicle and the stress on driver while also conserving fuel. A way to help drivers to park their automobiles in a disciplined manner is also inculcated in this paper.

– Despite enormous remote sensing technique available, leaf disease detection continues to be a real concern. This paper Proposes a method that uses computer vision based deep learning techniques to detect 15 categories of Leaf diseases for three types of leaves namely tomato, potato and pepper bell. For the proposed method different deep learning techniques such Modified Mobilenet, Xception, Inception_Resnet_v2 has been implemented for feature extraction, training, testing and appropriate detection of the leaf disease. Of all the above methods Enhanced mobilenet proves to be best in the detection of all 15 categories of diseases. The parameters obtained from mobilenet are more promising when compared to Xception, Inception_Resnet_v2. Using the state-of-the-art architecture considerable efficiency up to 97 percentage has be achieved.

Its really arduous work to simulate the shock wave interaction with boundary layer through high computational domains such as Large Eddy Simulation (LES), Direct Numerical simulation (DNS), Detached Eddy Simulation (DES) and so forth. This work comprise about numerical and computational analysis of supersonic flows where the Shockwave and Boundary layer interaction happens. Such flows uncover the presence of complex components, which should be painstakingly examined for the effective structure of Propulsion and Aerodynamic frameworks. Though, it has several flaws and efforts to acquire appropriate and effective results, the results are like precise and efficient to compare with real life experiments. In this paper the high performance computational simulation approach i.e., Large Eddy Simulation approach has used to detect, reveal and scrutinize the physical flow phenomena of shock boundary layer interaction mechanism over ObliqueImpingement (O-I) model with mach number (M) 2.7 and Reynolds number of 4300. The 3D flow structure is seen as instigated by the cleared SWBLI shaped on the sidewalls. The area of the endpoint of the episode shock close to the sidewall is restricted by a sweepback impact, permitting the meaning of an entrance Mach number M that is appeared to relate well with the spanwise degree of the centre stream. The acquired large-eddy simulation results have given a reasonable and exact proof of the essential adverse flow and the auxiliary detachment flow being basically tempestuous. Additionally, simulations uncover the nearness of such flow properties for the most part close to the shock foot and inside the distribution bubble. The wall effects are also studied along with sub physical characteristics such as adverse pressure gradients, interaction and re-attachment region, surface pressure distribution, expansion fan and so on. In the nutshell, the results are then compared with different angle impingements viz.9 and 12 Degree. Here, the Tecplot360 adhere a critical part for interfacing the post processor results and visualizing them through various plots, slices and frames.

Attendance management system is a necessary tool for taking attendance in any environment where attendance is critical. We can see most of the existing system is time consuming every time it requires human effort to take the attendance. Face recognition is an important application of Image processing owing to its use in many fields. Identification of individuals in an organization for the purpose of attendance is one such application of face recognition. Maintenance and monitoring of attendance records plays a vital role in the analysis of performance of any organization. The purpose of developing attendance management system is to computerize the traditional way of taking attendance. Automated Attendance Management System performs the daily activities of attendance marking and analysis with reduced human intervention. In our proposed system we will build an attendance system which will recognize the face of the student and check the appearance of the student face in the data archive and mark it as present or absent. Absent student information sent to their guardian by sending automatic message. as well as a mail sent to the staff describing number of student attending or missed the class. Thus, this project saves the time of the humans that will helps in saving maintenance and also generating report of absent and present student