IoT-BASED SPACECRAFT ANTI-COLLISSION TECHNOLOGY
IoT-integrated Spacecraft Anti-collision technology, invented and first successfully deployed by Bibhorr, constitutes five design sub-systems viz., Traffic Identification system (TIS), Density Evaluation Model (DEM), Trajectory Planning Model (TPM), Risk Assessment Model (RAM) and finally Heads-up Display (HUD) system.
The Traffic Identification Design uses a video imaging process based on an IoT-integrated video camera docked with a mathematical computing system. For the system to further handle the computational processes, raw image data feed as a first source impression is sent by the video camera. The working of the system involves recording image frames and sending them to the computer unit. The extraction technique includes an intensity reduction feature and the whole concept is used to divide a big collection of raw data and break it down into smaller, more tractable data sets for further subsequent processing. These huge data sets include a great number of variables, requiring a significant amount of processing resources to compute.
In the HUD screen, the dynamic density dT is visualized to the pilot, in form of a continuously varying graphical plot whose Y-axis denotes density variations and X-axis denotes the time.
The three-dimensionally dilated spatial frame consisting of n traffic elements is rendered in the density evaluation model. The frame, that encapsulates the elements, consists of magnitude a as three of its dimensions. Since the density is dynamic in nature as it changes over time ‘t’, it is a function of time, the magnitude of the three-dimensional spatial cube and number of traffic elements. This dynamic traffic density dT is mathematically incepted as: dT = 𝑓(𝑡, 𝑎, 𝑛)
In the risk assessment system model, the maximum collision probability risk P(C) is given as: P(C) = 𝑛ₐ/𝑛ₜ; where 𝑛ₐ implies the number of traffic elements tested for collision and 𝑛ₜ indicates the total number of traffic elements present in the rendered frame.
For evaluating the safe trajectory planning, FFT vertices are identified, two along dt and two along Dt. A computer-processed quadrilateral simulation is then established by extending interspatial lines through vertices and aligning the rest dimensions. Post the establishment of the empty zone ze, safe zone zs is computed using the below formula: zs = 𝑓(ze); where 𝑓(ze)= k√𝑧𝑒. Here k denotes the diminishing factor.
The transparent display feature mechanism which is visually layered within the windscreen of the spacecraft is well-highlighted by the HUD system. And its function is to display critical information and data directly in the vision feed of pilot without distracting the pilot from the usual vision angle onto the screen.