UNIT LEARNING OUTCOMESTwo ‘Unit Learning Outcome (ULO)’ of this unit are (ULO2) develop strategies using generic and IT specific techniques toexplore algorithms and (ULO3) Create algorithms using the input-processing-output model, defining diagrams andpseudocode to demonstrate simple program design.This assignment requires you to design and develop algorithms using pseudocode. The assignment will indicate whetherstudents can partially attain the associated Unit Learning Outcomes.INSTRUCTIONSRead the entire assignment sheet, the rubric and answer all the following tasks below.Place your name, ID and answers in your document. Please note that only MS Word (docx) may be submitted. The wordcount is 1500 words max (upper limit), so be concise and efficient!Submit your assignment document on CloudDeakin applied project dropbox.INTRODUCTIONJetstar has chosen Boston Dynamics as the vendor to produce the UAV (Unmanned Aerial Vehicle) passenger plane discussed inthe critical thinking task. The project is now being broken down into segments (divide and conquer) by the project manager. Theyhave outlined that one major part of this project is to develop the algorithms (artificial intelligence) to operate the UAV and ensure itdoes what it is designed to do safely and successfully. So, your first goal as the software developer is to create two algorithmmodules in a pseudocode format. At a later stage these algorithms will be implemented into the UAV allowing it to perform specifictasks safely and accurately.APPLIED PROJECT: DESIGN THE UAV PASSENGER PLANE ALGORITHM!The purpose of this applied project is to begin to develop the overall algorithm for the UAV, however, this will begin with developingfunctionality for only two main operations, one easier and one more difficult described below (you will need a variety of modules).Your algorithm should have a Main()+END where all sub-modules will be launched from.TASK 1 – FUNCTIONALITY: FACIAL RECOGNITION (BEGINNER / INTERMEDIATE)1. The first functionality is focused around automated boarding of passengers. So, the approach is to use a facial recognitionalgorithm to verify the identity of passengers – E.g. board_passengers(passenger_database).2. Focus on the steps involved to check the passenger’s passport photo vs. the characteristics of what the person’s facelooks like on camera (think of a typical Australian airport procedure). If they positively match, the passenger can board butif they are different they will not be permitted on the UAV – E.g. Facial_recognition(passenger, passport).Hint: You can see what a typical Australian passport looks like (sourced from Government website):https://www.usi.gov.au/sites/usi/files/inline_img/15/10/passport.jpgHint: Check things like eye colour, hair colour, skin colour and nose/mouth shape.