https://drive.google.com/drive/folders/17epZg_Gj7G8ql8GCYAAY9q77OCmWahlk?usp=sharing

https://drive.google.com/file/d/18BtHTEUdxHgm7Y2XZ4Zx3duoh17euc0c/view?usp=sharing

Project Summary :

Our solution for the “ TAKE FLIGHT “ challenge is a combination between software algorithms and hardware components represented in a mobile app and digital twin IoT system using some additional sensors to collect more data for future improvements in such an innovative way that helps the climate change problem and the green renewable industry sector so we could help reduce the co2 emissions; after we get the data from NASA's airborne campaigns that collect high-resolution data, we analyze it and the most benefit of this data by understanding the climate in the specific region where we can build either solar power station or wind farm station ( offshore / onshore ) and this depends on the choice of the user.

the app targets :

1- wind turbine companies 

2- solar energy companies 

Our vision is to use those modern new technologies to help the globe solve the Energy problem and apply more alternative resources in our life, this idea will serve the SDGs Spirit  

Goal 7: Affordable and clean energy

Goal 8: Decent work and economic growth

Goal 9: Industry, Innovation and Infrastructure

Goal 13: Climate action

Eureka means “ I have found it! “ which is an ancient Greek word used to celebrate a discovery or invention. attributed to Ancient Greek mathematician Archimedes. so, here we tried our effort to discover a new solution for the challenge like Archimedes did 

The Number 369 is from the Great scientist of all times “Nicole Tesla “ as we try to achieve his remarkable quote “ If you want to find the secrets of the universe, think in terms of energy, frequency and vibration.” where here we use the integration of modern technologies like IoT, AI, Digital twin and  Industry 4.0  so we shall achieve that quote 

How We Addressed This Challenge : 

Introduction :

Today, I have a story about a land. That land embraced us for thousands of years and gave us life, and a food source to survive… Being able to work, Create, Build, and evolve as in the vast universe, every creature relies on this own Environment to find his way to survive; the earth is not just a floating Magnificent planet in our galaxy with a lot of locked secrets but, also the key to continuously updated future for all living creatures.

Problem:

 Did you know that NASA uses aircraft to study the Earth every day? Not all the public knows the answer …. NASA‘s Airborne data fill the gap between ground-based and satellite-based measurements to answer questions about our planet. Where the five NASA campaigns use airborne data, as well as other types of data to address a variety of environmental issues in different geographic areas ; 

the problem of this challenge we can divide into two main points :

1- NASA’s website is not streamlined or simplified for use by the general public due to the vast number of parameters, time averages, and statistical reports available 

2- the public doesn't understand how important is the data to solve problems associated with Earth’s changing climate; as they don't know to imagine a clear visible way they use this data  

And here comes our mobile app solution that facilitates the importance of the data in the industry sector, especially the green renewable energy using technologies IoT, AI, Digital twin and  Industry 4.0

and here we used the user data to make proof of evidence through a real case study for the USA we choose California state, and for local, we test Aswan city in Egypt and the reason for selection is that both cities are real applications for renewable energy places

California case study :

Aswan Case Study :

those insights from the data we can apply on a larger scale in

Industrial usages:

In solar energy generating stations:

1. Getting maximum benefit from solar radiation to rapidly develop and revive the economy.
2. Giving global alternative clean solutions for energy shortage issues using GPS, Date and Time algorithms in the industry by using the AI algorithms to know the suitable spots to install solar energy stations 

In wind turbine generating stations:

1. Predict the speed of the wind, air humidity, temperature and pressure upon analyzing the data coming from NASA planes and using a Trained ML model so it helps you choose the perfect spot to build the power station 

Using Digital Twin to give real imagination for the place you chose to build the power station

Methodology:

First stage :(initial step )

1- The Collected Data from NASA’s Planes are recognized and used through location detection theses data goes through a cleaning and scraping process so we can understand it clearly and then be able to analyze and visualize it on the mobile app 

2- then we see if any of the data is missing or if there is a relation between any variables or if the data contains photos so we can use Computer vision and AI To accelerate analyzing of data with high accuracy and effectively then from the data provided we get the radiation intensity, water info and GIS info. 

3- after that the user chooses from either a solar energy system or wind energy system; he gets the purpose of these data in an industrial way ( solar power stations - onshore wind farms - offshore wind farms )

Second : (Linking step )

you use GPS to locate the area, then through API algorithms in our app link you with the suitable readings according to the purpose of applying:

Solar Example :

1-radiation intensity

2-the number of panels you need to set up your solar energy system

3-approximate setup costs

4-needed battery capacity for setup

Wind Example :

1-Wind speed and direction 

2-Air humidity, temperature, Atmospheric pressure 

3-approximate setup costs

4-The needed number for that setup

Third :  ( Digital Twin )

if the user wanted to see if the selected spot will be suitable for how many elements whether solar system or wind system the user can click on the button ” show “ to simulate the digital twin feature showing the expected number of stations based on the prediction made from the Trained ML model and the described data is labelled beside the elements 

A digital twin is a digital representation of a physical object, process or service. A digital twin can be a digital replica of an object in the physical world, such as a jet engine or wind farm, or even larger items such as buildings or even whole cities.

As well as physical assets, digital twin technology can be used to replicate processes to collect real-world data to create simulations that can predict how a product or process will perform. And with the integration of theinternet of things (Industry 4.0), artificial intelligence and software analytics to enhance the output.

The concept of digital twins was first put forward in David Gelernter’s1991 book ‘Mirror Worlds,’ with Michael Grieves of the Florida Institute of Technology going on to apply the concept to manufacturing.

By 2002, Grieves had moved to the University of Michigan when he formally introduced the digital twin concept at a Society of Manufacturing Engineers conference in Troy, Michigan.

However, it was NASA that first embraced the digital twin concept and, in a 2010 Roadmap Report, John Vickers of NASA gave the concept its name. The idea was used to create digital simulations of space capsules and crafts for testing.

The digital twin concept spread further still in 2017 when Gartner named it one of the top 10 strategic technology trends. Since then, the concept has been used in an ever-growing array of industrial applications and processes. These digital twins are then used to monitor the system and for predictive maintenance using machine learning algorithms, where possible system failures can be predicted earlier and therefore be handled better.

fourth : (smart microgrids )

--> In old grids send power in one direction from producer to consumer.

Smart grids depend on a 2-way communication network providing instantaneous feedback on system-wide operations, power interruptions & electrical use back.

--> features:

1- real-time monitoring: measure and analyze electricity usage: 2-way communication network with the grid influencing and being influenced by other components, it also provides a potential way to shift from flat-rate fees for electricity in favour of time-of-use pricing.

2- stability and automated management: demand response addresses not the only concern of the grid components as potential problems range from downed trees, unexpected failures at power plants, or even attacks by malevolent parties as the extensive metering network can identify problematic conditions before any service disruption or equipment damage occurs as it acts accordingly prevent issues that need independent resolutions through pattern recognition and nuanced identification of grid conditions.

3- power storage management: there would be power storage units to store the power generated by PVs or wind turbines then we could use this power later or sell it and the smart grid will start to earn money.

the above photos show the importance of power storage management by the famous entrepreneur Elon mask and show the benefits of batteries here in our solution the smart micro grids satisfy that purpose

we look forward to adding some technological approaches to secure that the system is safe from fishing attacks and human fault

fifth: (future work)

--> add more features so the user can control the grids through the app.

--> work on a more efficient model to predict the change effects on renewable energy.

--> work on updates to control systems to be more efficient.

--> add security features to avoid human mistakes and cyber attacks.

Future Aims and Features hopped to be used:

we aim for our solution to have key partners so we can integrate with the market and the other startups … one of those aims :

1. Make partnerships with existing companies so we become viral 
2. Use Advanced Technologies in maintenance and machine diagnosis prediction 

Companies:

•  EMROD 

in The future hope that we can apply the concept of long-range wireless power transferring technology offered by EMROD; As that trial will open many doors of innovation to solve many related science and industrial topics as EMROD try to achieve Nikola Tesla‘s dream 369 

As the future is clean wireless energy and EMROD is perfectly positioned to become a leader in this huge market 

Advanced Technologies:

•  Using AI algorithms in Maintenance, machine diagnosis prediction and vibration data analysis … as this represents a critical aspect of manufacturing systems. Its optimization may lead companies to save costs related to production losses and can extend the whole lifecycle of assets or components. This paper aims at proposing a methodology for evaluating the behaviour of systems for maintenance purposes by means of analysis carried out on real vibration data collected in the work environment. For this purpose, a digital twin approach has been developed and the statistical method of the control charts has been integrated to conduct the analysis of the vibration data. The methodology has been applied to a real case study in order to analyze the behaviour of an electric motor used in the industrial sector and the results show that the method is effective in predicting possible failures that can lead to applying preventive maintenance actions

finally, we try to make the idea more visible by taking steps in startup ideation and making a simple Business model Canvas

and here is the link for BMC --> https://canvanizer.com/canvas/wRjhCXvYoc0rd?fbclid=IwAR1DeKNwSrMJK5VS7C2xNUXMaZPIAquzUw6C_Tac5ELIsBhH0JdmtZ1osYk

• For the space agency data, we used some provided by NASA in the challenge this year; we also used some websites offered by NASA, but we defined them as external ones 

Provided by Nasa :

1. https://asdc.larc.nasa.gov/project/FIREX-AQ
2. https://www.earthdata.nasa.gov/ 
3. https://search.earthdata.nasa.gov/search 
4. https://impact.earthdata.nasa.gov/casei/ 

External Resources :

1. https://power.larc.nasa.gov/ 
2. https://www.energy.gov/ 
3. https://en.wikipedia.org/wiki/Solar_tracker 

We used the data provided from the previous links to understand how different climate variables changed over the years and how these changes affect some of the renewable energy technologies like wind turbines and solar panels, we also used other external data sources like Kaggle to create machine learning models capable of predicting failures early in wind turbines.

The team has its Diversity which we believe is the "Secret Sauce" to Success;

 we are coders, makers, R&D engineers and innovators; who want to make the best access from (NASA’s) free and open data to help in solving real-galactic world problems and help in taking action and that's why our slogan is “ our climate our unity “; as it Seven Billion Dreams. One Planet. So we must Consume with Care

our journey during the hackathon is based on distributing the duties among us so we can handle the estimated time 

Also, we want to make it a memorable hackathon; as we believe positive vibes with effort do change the workflow; and work as a team mentality not as personal affairs, solution for the challenge is not just a link between industry and the user.... no its a global multi-vision purpose to make unique startups that facilitate the life so it can be applied in real life, and we get benefitted from the proposed idea to make the world a cleaner place and let the next generation be a better version of themselves

The software references for the basic solution:

• A mobile app that shows and educates the public about a problem associated with Earth’s changing climate where we use the flutter platform to do that

• The app uses AI algorithms to show the best spots for building solar panel stations, onshore wind stations or offshore wind stations of your preference then let the user know more details about the selected station 

Hardware and IoT Sensors references :

For solar system :

1. Temperature, Rain, LDR and Air Quality Sensors
2. NEMA 17 stepper motor 
3. Coupler 30 mm 
4. Ardunio and controlling electric unit 
5. Batteries management system    
6. Connection wires 

The Add solution we will try to do :

1. Using IoT sensors in the solar sector, especially the single-axis tracking systems to make an end-to-end idea from showing the data on the mobile app to monitoring the machines and power stations remotely and the smart microgrids

1. Here is a contribution to scaling the idea on end to end solution large scale; we tried to make a single-axis solar tracking system to implement and validate the solution more, as for the movement we used LDR sensors to track the sun and a stepper motor for high torque all that is controlled with Arduino to facilitate the process and for the tracking mechanism we applied the tracking equation so we make the most efficient of the panels

this handmade solar tracking system also demonstrates the concept of AI Maimtance prediction problems

or wind system :

1. Temperature, Air Quality, Pressure, Humidity and Water Quality Sensors

We used those Sensors in the prototype so we could explain the idea more efficiently.

software and code :

GitHub --> https://github.com/El-Helbawy-M/Nasa-App/tree/main

#hardware #flutter #solar_tracking_system #APIs #artificial intelligence #iotsystems #data_analysis #sdgs#global_judging#climate_change#BMC#bussines#entrepreneurship #renweable_energy#digital_twin