Sky Map
By: Daanish Peerkhan
Tags: Astronomy, Skymap, Data Science

Project

This is an open source project in which we will be mapping the sky using Deep Learning, Neural Network, Python as the software to compute the data obtained from a wide array of telescope network or a VLBI ( very-long-baseline interferometry).

A sky map is a tool used by Astronomers to maintain a record of different objects in the sky with their dynamic coordinates.

Market Demand

There are many precise sky maps available throughout the internet and astronomy archives. But, their problem is that, the data in those maps are crowded, i.e. there is too much data to accurately use them. For example, if you just look in our own astronomy chart (click link), you can see there are many objects that aren’t even visible to us through naked eye. Hence, to minimize this problem we will create a new sky map which can be accurately used for astronomy (from Earth). This map will reduce the unwanted data from current sky maps and make them more user centred.

Current Maps

There are many apps available on Android and IOS that has Sky maps integrated, like Starry sky, Sky portal, Night Sky etc. These maps are very advanced as they all are based on the same survey map and features the same data crowdedness as mentioned before. These maps are very difficult to operate due to so much data being presented to users at the same time without actually displaying real time objects.

You can check out such example on my website (Click).

Pricing

We will divide this section into two parts:

Server end Community end

Details

On the server end we will require web hosting that will cost around $13 / month and then we need a powerful computer that will cost around $1000. On the community end we have Motor Drive which will cost around $100 each. So, the total cost will depend on the number of people in the community. This can be calculated using this equation. Total Cost = 1000 + 100*n , where n is total number of users(nodes).

Technologies Used

Hardware

Commercial telescopes of any aperture(As many as possible for scalability of VLTI). Motor Drive (Telescope Automation) Raspberry Pi (For local data processing) High Computational power system (For data processing at large scale), preferably one equipped with CUDA cores for image processing. Data Centre, for Image storage (Omit if using Cloud storage).

Software

JavaScript, PHP, CSS, HTML (For website). Python 3.x (For image detection code) Keras library (For machine learning program) Tensorflow Library GPIO library (For Raspberry Pi motor controller) Stellar Classifier (Base code for Image detection) Keras model (.h5) from google tool.

The Plan

We will start by creating a astronomy community, in order to have many individuals working on this project. This is a very necessary step in order to obtain the data-set for our sky model, as these people are the ones who will capture images of the sky through their telescopes. We need at least few thousand of people in order to have a great accuracy. This community will be created online using website and social media to attract as many people as possible. We will develop a website first using HTML5, CSS, PHP and JavaScript for a dynamic website. This website will be the place where our participants (People who will collect data for this project) will upload data, chat with the community, Q&A with other members and convey our cause and mission. You can find our website here.(click link) After this we will develop a proto-type of our telescope motor-drive system, using Raspberry Pi and DIY motors. For software we will develop a python script using GPIO and OPENCV libraries for motor control and image storing. Also, we need another program to store the data with geographic and astronomical data like coordinates of the user and time which will be used to determine the Azimuth and Elevation of the picture. As soon as our proto-type motor drive is ready we will make a documentation for it so, that our members can then follow this documentation and set up their motor drive system. The motor drive consists of camera module. After collecting data, we will train a machine learning model using the tool specified in the software requirement. Now that we have our keras or .h5 model we are ready to carry out our detection part. For this section we will use our stellar classifier program and store the result with their meta data. Now that we have all the data required for our map, we will finally plot it using another python library called as skymap for map plotting. This will take some time as we have thousands of data sets to work on. As we cannot carry this process on our local computer we will be using Google Collab or rent a super computer.

ERROR: 500

Yeah, 500 error what? So, a 500 error is a webpage error code that is returned due to some server issues. But, over here it is meant to convey possible errors that can occur in this project. :)