Developing Innovative Project Management Dashboard, Internet of Things, and Image Mining

Innovative project management dashboards enable to gather, perceive, compile, process and report project-related data using various tools such as the Internet of Things (IoT). These platforms are essentially customizable and can take various modern project management approaches, including lean, agile, scrum, Kanban, etc. These dashboards are apt for data collection, storing, and categorization according to a predefined level of access throughout the project. The main advantage of these dashboards is representing the processed data in the format of visual infographics, conveying a considerable amount of information at a glance. Moreover, these systems can provide independent data storage, integrity, security, multiple accessibilities, instantaneous data accessibility, and data recovery after data crashing.

As technology progresses, the internet becomes ubiquitous, meaning any piece of the electronic device in human life can connect to the internet and transmit data. To put simply, IoT means digital interaction and data exchange of a set of sensors to improve the quality of human life processes and procedures. There are always a couple of sensors for data gathering in the IoT ecosystem. The collected data must be compiled and integrated into the central data hub to meet the processors' requirements. Then, through web-based processes and computations, the resulted output would be presented in the appropriate final gateway. Fortunately, artificial intelligence (AI) application facilitates the compilation of a massive amount of data in real-time, leading to a continuous flow of data from sensors to processors. IoT applications include but are not limited to:

  • Infrastructure health monitoring
  • Equipment condition monitoring
  • Intelligent supply chain
  • Energy usage optimization
  • Project progress control/monitoring

 

Image usage is surging in human life. Images taken from a part project convey a significant amount of information from the actual scene. These shots can be used for reporting, coordinating, and even as proof against possible allegations. It should be noted that the perceived information from an image by the human brain is far more sophisticated than computers. Computers see images as tensors and need to extract semantic information using computer vision algorithms. Computer vision is a subset of AI enabling computers to see and perceive the world by digital images. This potential enables us to employ the computer vision for engineering purposes as such as:

  • Measurement and calibration
  • Quality control and defect detection
  • Object detection and tracking
  • Activity recognition
  • Scene reconstruction
  • Safety monitoring
  • Object segmentation
  • Digital twining

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