**Introduction**In this final part, we will integrate all components to measure the speed of vehicles in front of you. We will also use GPS data to enhance accuracy.

**1. Calculating Speed**To calculate the speed, you need to measure the distance traveled by the vehicle over time.

`import time previous_time = time.time() previous_distance = None def calculate_distance(bbox): # Custom function to calculate distance based on bbox size # This is a placeholder for the actual distance calculation logic return bbox[2] - bbox[0] def calculate_speed(distance_initial, distance_final, time_elapsed): distance_change = distance_final - distance_initial speed_m_s = distance_change / time_elapsed speed_kmh = speed_m_s * 3.6 return speed_kmh`

**2. Integrating GPS Data**Use the smartphone’s GPS to get your vehicle’s speed. This can be done through various Android APIs or libraries.

`# Placeholder for getting the vehicle's speed from GPS def get_my_vehicle_speed(): return 50 # Assume a constant speed for demonstration`

**3. Combining Everything**Combine all the components to calculate the relative speed of the vehicle in front.

`while cap.isOpened(): ret, frame = cap.read() if not ret: break results = model.predict(source=frame) bboxes = extract_bboxes(results) outputs = deepsort.update(bboxes) current_time = time.time() for output in outputs: bbox = output[:4] track_id = output[4] current_distance = calculate_distance(bbox) if previous_distance is not None: time_elapsed = current_time - previous_time relative_speed = calculate_speed(previous_distance, current_distance, time_elapsed) my_vehicle_speed = get_my_vehicle_speed() front_vehicle_speed = my_vehicle_speed + relative_speed print(f'Front Vehicle Speed: {front_vehicle_speed} km/h') previous_time = current_time previous_distance = current_distance`

**4. Enhancing Accuracy**

**Calibration**: Calibrate your system to improve accuracy.

**Frame Rate**: Ensure the video processing frame rate is high to minimize latency.

**Conclusion**By following this series, you have learned how to build a system to measure the speed of vehicles in front of you using a smartphone. This involves capturing video, detecting and tracking vehicles, and calculating their speed using real-time data.

**FAQ**

**How do I calculate the speed of a vehicle?**Speed is calculated by measuring the distance traveled over a period and then dividing this distance by the time taken.

**How can I integrate GPS data into my system?**You can use GPS data to get the speed of your vehicle and then calculate the relative speed of the vehicle in front by comparing positional changes over time.

**What are the challenges in real-time speed calculation?**The main challenges include ensuring low latency, accurate distance measurement, and handling varying frame rates and environmental conditions.

**How do I enhance the accuracy of my system?**Calibrating your system, ensuring high frame rates, and using precise distance measurement methods can significantly enhance accuracy.

**References**

- Basics of Speed Calculation: Physics Classroom

- Using GPS for Speed Measurement: GPS World

- Real-Time Video Processing: OpenCV Real-Time Video Processing

By following this structure, each part of the series will provide a comprehensive overview, practical implementation steps, and additional resources for further learning. This approach ensures that readers of all levels, including high school students, can understand and apply the concepts.