Name of the prototype AURA(short for

Ideas for Solving the Problem (AURA)

Speech-to-Text Conversion: Utilizing speech recognition algorithms to convert spoken words into text.
Speaker Identification: Implementing techniques to differentiate between multiple speakers in noisy environments.
Real-time Language Translation: Integrating machine translation capabilities for multilingual support.
Miniaturization and Wearable Design: Designing a compact, user-friendly device in the form of a watch.

Solution Steps (AURA)

Step 1: Sound Acquisition and Conversion

The MEMS microphone captures sound waves and converts them into electrical signals representing capacitance variations. These variations are processed by the ASIC (Application-Specific Integrated Circuit) which transforms them into a digital signal.

Step 2: Speech-to-Text Processing

The digital signal is fed into a speech recognition algorithm. This algorithm processes the audio data and converts it into text, which is then displayed on the OLED screen.

Step 3: Speaker Identification (Optional)

If multiple speakers are detected, a speaker identification algorithm analyzes the audio characteristics to identify the individual speakers. This information can be displayed alongside the transcribed text.

Step 4: Language Translation (Optional)

If language translation is selected, the transcribed text is fed into a machine translation engine. The translated text is then displayed on the OLED screen in the user’s chosen language.

Final Answer (AURA)

The AURA prototype uses a MEMS microphone, ASIC, and speech recognition algorithms to convert spoken words into text, optionally identifying speakers and translating the text into other languages. The results are displayed on an OLED screen integrated into a watch-like device.

Highlights (AURA)

The use of a MEMS microphone allows for low-power consumption and miniaturization.
The integration of speaker identification and language translation enhances the device’s functionality.
Potential challenges include accurate speech recognition in noisy environments and the computational demands of real-time translation.

Ideas for Solving the Problem (NOVA)

Notification Management: Developing a system to collect, prioritize, and deliver notifications from various sources.
Task and Schedule Management: Implementing features for setting reminders, scheduling tasks, and managing daily routines.
Voice Interaction: Utilizing speech recognition and text-to-speech capabilities for user interaction.
Environmental Data Integration: Incorporating weather data and other environmental information.

Solution Steps (NOVA)

Step 1: User Interaction and Data Input

The user interacts with NOVA via voice commands or touch input. The MEMS microphone captures voice commands, which are processed by a speech recognition engine.

Step 2: Task and Schedule Management

The system processes user input to create and manage tasks and schedules. This involves setting reminders, prioritizing tasks, and organizing the user’s daily routine.

Step 3: Notification Delivery

NOVA delivers notifications via voice output (using the Arduino speaker) or text display (if applicable). Notifications include reminders for tasks, schedules, and weather updates.

Step 4: Environmental Data Acquisition

The DHT11 and BME280 sensors collect temperature, humidity, and pressure data. This information is used to provide weather updates to the user.

Final Answer (NOVA)

The NOVA bot uses a combination of voice interaction, sensors, and task management algorithms to help users organize their schedules, manage tasks, and receive timely notifications, including weather updates.

Highlights (NOVA)

The integration of multiple sensors provides comprehensive environmental data.
The use of voice interaction makes the system user-friendly and accessible.
Potential challenges include ensuring accurate speech recognition and managing a large number of notifications effectively.

Ideas for Solving the Problem (ThermoGuard)

Temperature Monitoring: Using a thermocouple to accurately measure the temperature of the appliance.
PID Control: Implementing a PID controller to maintain the desired temperature and prevent overheating.
Overheat Protection: Utilizing a solid-state relay (SSR) to cut power to the appliance if the temperature exceeds a safe threshold.
Hardware Selection: Choosing appropriate components such as a microcontroller, MOSFET, and SSR for reliable operation.

Solution Steps (ThermoGuard)

Step 1: Temperature Measurement

The Type K thermocouple measures the appliance’s temperature and sends the data to the microcontroller.

Step 2: PID Control Algorithm

The microcontroller uses the PID algorithm to compare the measured temperature to the setpoint. The algorithm calculates the necessary adjustments to maintain the desired temperature.

Step 3: Power Control

Based on the PID output, the microcontroller controls the MOSFET, which in turn controls the power supplied to the heating element via the SSR. If the temperature exceeds the setpoint, the SSR cuts power to the appliance.