Designing an IoT Solution for Solar Panels and Sun-Tracking

Your assignment must be submitted electronically via BlackBoard (Assignments tab) by the submission time. The report should be contained in a Word document or PDF. No other means of submission will be accepted. The software code will be submitted independently. Any assignment submitted late but within 5 working days of the deadline will be given a maximum mark of 50%. Assignments submitted more than 5 working days after the deadline will not be marked, and a mark of 0% will be recorded.

Learning Outcome to be assessed:

1 Research, analyse, integrate, apply and present detailed design proposals.

2 Use appropriate technical terminology to describe basic design concepts.

3 Develop technical competence and skills in the generation and adaption of design ideas.

In response to global warming, IoT technology is witnessing rapid progress in applications and implementations in many industries. Advanced IoTCloud (AIC) specializes in IoT solutions and has experience deploying total solutions for many industry disciplines, including medical and transports solutions.

The AIC has hired you to design an IoT solution for solar panels, sun-tracking in addition to sensors monitoring and diagnosis. The sensors that need to be attached to the solar panels include solar irradiance's sensory and the solar panel's surface temperature network. The solution should consider the cloud implementation in this IoT solution regarding the monitoring and the diagnosis.

Provide a detailed, professional report for your company that contains the following:

1. Design. Introduce your solution, provide the necessary block diagram/s, flowcharts, and justify each of the solution elements' choices.
2. Communication Solution. Suggest the necessary communication media and the communication protocol/s that can be used for this solution and justify your choice. The devices you choose for the solution must support the suggested communication protocols.
3. Temperature Sensors functionality diagnosis. Suggest a method to detect if the temperature sensor is not working using machine learning algorithms. This test can be performed by simulating signals representing a healthy signal and others that are not healthy.
4. Machine Learning. Discuss the implementation of the machine learning algorithm that you will use for sensor functionality diagnosis at the edge of the cloud. Support your discussion with the necessary graph that supports your implementation.
5. Fuzzy Logic Components. Explain all the fuzzy logic components (e.g., inference method, membership functions) employed in your application using required scientific terms.
6. Fuzzy logic-based controller. Build an application using Fuzzy logic to establish autonomous decision-making to optimize the solar panel orientation. This smart application is supposed to input:
7. Data from local sensors, and
8. To control how much the solar panel should be directed to the sun, that produces the highest power within an acceptable temperature range.
9. Matlab: Develop an interface test platform to show that your system works as desired and ready to be incorporated into a grid using the fuzzy logic built in Section
10. Design Features. Explain why a customer should buy the solar grid solution you are suggesting, making your solution head and shoulders over the other off-the-shelf smart solar systems reviewed in Section. The Department’s Principles of Assessment will be used to determine grading levels.

1 Design. Introduce your solution, provide the necessary block diagram/s, flowcharts, and justify each of the solution elements' choices. 10%

2 Communication Solution. Suggest the necessary communication media and the communication protocol/s that can be used for this solution and justify yourchoice. The devices you choose for the solution must support the suggested communication protocols.

3 Temperature Sensors functionality diagnosis. Suggest a method to detect if the temperature sensor is not working using machine learning algorithms. This test can be performed by simulating signals representing a healthy signal and others that are not healthy.

4. Discuss the implementation of the machine learning algorithm that you will use 10% for sensor functionality diagnosis at the edge of the cloud. Support your discussion with the necessary graph that supports your implementation.
5. Fuzzy Logic components. Explain all the fuzzy logic components (e.g., inference method, membership functions) employed in your application using required scientific terms.
6. Fuzzy logic-based controller. Build an application using Fuzzy logic to establish autonomous decision-making to optimize the solar panel orientation. You can use any programming language you are comfortable with. This smart application is supposed to input:
7. Data from local sensors, and
8. To control how much the solar panel should be directed to the sun, it will produce the highest power within an acceptable temperature range.

Explain why a customer should buy the solar grid solution you are suggesting, making your solution head and shoulders over the other off-theshelf smart solar systems reviewed in Section.