Grafana is an open-source web application specialized in time-series visualization. Hence, it is suitable for the the purpose of monitoring. One of interesting facts is that Grafana is a fork from Kibana 3 to enhance the ability of dashboard editing and make it as a clean and elegant time-series visualization tool. To get the sense of Grafana dashboard, surf this link: https://play.grafana.org.
When do researching to choose a good data storage technique for log collection, searching and analytic; I found elasticsearch is a ideal choice because of following reasons:
Default Apache Nifi installation comes without security layer which exposes the development UI. As a result, users can freely access the Nifi project development with knowledge about the hostname and binding Port. You can see two potential security risks:
The goal of this project is to collect and visualize the stock price of all tickers in Vietnam. There is quite limited access to API for a single business user, this project aim at scrap data from website, clean, extract and load into data warehouse. The final product is a maintainable/reliable data pipeline with exposed analytic dashboard hosted on cloud, and end authorized users can access to 24/7 with daily updated data.
This project aims at recognizing the car make and model based on a Stanford Cars Dataset with 16,185 images. This dataset includes information about car make, model, and year (Eg. 2012 Tesla Model S) with 196 different classes. However, in this project we target to identify the car make and model only; this results in 164 different classes in total.
This project describes a computer based system that utilizes a 3D sensor to bridge the communication barrier between hearing (and/or speech) impaired people and hearing ones. Above figure shows how I love Vietnam demonstrated in Vietnamese Sign Language.
This project aims at implementing an intelligent human resources management system which combines the RFID and face recognition method. The proposed system will have a camera to capture the faces of people and a RFID reader to check the ID numbers. If both of the verifying processes return a “Pass” signal, then a successful entrance signal is generated.
This project targets at applying the state-of-the-art technology in computer vision which is depth sensor equipped with RGB camera called Kinect. Kinect is not only normal camera sensor but also a special device can provide depth map. Depth map is acquired through OpenNI library then processed by Point Cloud library to extract accurate information about the environment.
This project provides an alternative way for robot to detect and estimate the distance to an object. The stereo vision technique is used as human eyes with the support of OpenCV library.
The project was part of my subjects in University time back then in 2011 when I did so many computer vision related projects.
Update your browser to view this website correctly. Update my browser now