Sensor fusion basics in EV Technology - Mini Project: Build & Apply

Sensor Fusion Basics

📖 Scenario: You are working on an electric vehicle (EV) system that uses multiple sensors to understand its surroundings better. Combining data from these sensors helps the vehicle make safer and smarter decisions.

🎯 Goal: Build a simple sensor fusion setup that collects data from two sensors and combines their readings to get a clearer picture of the environment.

📋 What You'll Learn

Create a dictionary called sensor_data with two sensors and their readings

Add a variable called confidence_threshold to set the minimum confidence level

Use a loop with variables sensor and reading to filter sensor readings above the threshold

Create a final dictionary called fused_data with only the sensors that meet the confidence threshold

💡 Why This Matters

🌍 Real World

Sensor fusion is used in electric vehicles to combine data from multiple sensors like cameras and lidars to improve safety and navigation.

💼 Career

Understanding sensor fusion basics helps engineers and technicians develop smarter EV systems that can better detect obstacles and make driving decisions.

1

Create initial sensor data

Create a dictionary called sensor_data with these exact entries: 'Lidar': 0.85, 'Camera': 0.75

EV Technology

# Create the sensor_data dictionary with Lidar and Camera readings
# Your code here

Need a hint?

Use curly braces to create a dictionary with keys 'Lidar' and 'Camera' and their confidence values.

2

Set confidence threshold

Add a variable called confidence_threshold and set it to 0.8

EV Technology

sensor_data = {'Lidar': 0.85, 'Camera': 0.75}
# Set the confidence_threshold variable
# Your code here

Need a hint?

Use a simple assignment to create the confidence_threshold variable.

3

Filter sensor readings by threshold

Use a for loop with variables sensor and reading to iterate over sensor_data.items() and create a dictionary comprehension called filtered_sensors that includes only sensors with readings greater than confidence_threshold

EV Technology

sensor_data = {'Lidar': 0.85, 'Camera': 0.75}
confidence_threshold = 0.8
# Create filtered_sensors dictionary comprehension
# Your code here

Need a hint?

Use dictionary comprehension with for sensor, reading in sensor_data.items() and an if condition.

4

Create final fused data dictionary

Create a dictionary called fused_data and assign it the value of filtered_sensors

EV Technology

sensor_data = {'Lidar': 0.85, 'Camera': 0.75}
confidence_threshold = 0.8
filtered_sensors = {sensor: reading for sensor, reading in sensor_data.items() if reading >= confidence_threshold}
# Assign filtered_sensors to fused_data
# Your code here

Need a hint?

Simply assign the filtered_sensors dictionary to fused_data.