Unlock the True Potential of Meraki MV Cameras with AI and Computer Vision
In today’s fast-paced world, simply having surveillance cameras isn’t enough. What if your cameras could not only record but also understand and interpret what they see? This isn’t a vision of the future—it’s happening now. By leveraging artificial intelligence (AI) and machine learning, your Cisco Meraki MV cameras can be transformed into powerful, intelligent surveillance tools.
The Power of Meraki MV Cameras
Meraki MV cameras are known for their robust performance, ease of use, and advanced analytics. For example, it can detect audio, light intensity (LUX level), people and car (and count them) by default. Further potential can be unlocked when Meraki MV is coupled with cutting-edge AI technologies. This transformation is made possible through computer vision and deep learning capabilities, specifically using OpenCV and pre-trained models from the COCO dataset.
How It Works
- RTSP Streaming: Meraki MV cameras can stream live video using Real-Time Streaming Protocol (RTSP).
- External Processing: The RTSP feed is routed to an external system running OpenCV, equipped with pre-trained models from the COCO dataset.
- Object Detection: This setup allows for real-time identification and classification of 80 commonly recognized objects using the YOLO (You Only Look Once) object detection model.
- Actionable Insights: Detected objects can trigger alerts, automate processes, and provide valuable data for analysis.
Real-World Applications
The integration of AI and computer vision with Meraki MV cameras opens up numerous possibilities:
- Enhanced Security: Automatically detect unauthorized access, suspicious activities, or specific objects, and instantly alert security personnel.
- Retail Optimization: Monitor customer behavior, manage inventory, and optimize store layouts by analyzing interactions with products.
- Traffic Management: Improve urban planning and traffic control by analyzing vehicle and pedestrian flows.
- Industrial Automation: Oversee manufacturing processes, monitor safety compliance, and improve operational efficiency by detecting specific objects and anomalies.
The Future of Surveillance is Here
By integrating Meraki MV cameras with OpenCV and YOLO, surveillance systems evolve from passive monitoring to proactive, intelligent solutions. This powerful combination of AI and machine learning not only enhances security but also provides actionable insights, making your surveillance system smarter and more responsive.
Are you ready to elevate your surveillance game? Embrace the future with AI-powered object detection and see the world through smarter eyes.
The 11 lines of python code below shows how simple to use Meraki’s RTSP stream to detect objects using COCO data set.
import cv2
import cvlib as cv
from cvlib.object_detection import draw_bbox
#live camera feed from Meraki camera via Real time streaming protocol (RTSP)
video = cv2.VideoCapture("rtsp://[your rtsp ip address]/live")
while True:
ret, frame = video.read()
bbox, label, conf = cv.detect_common_objects(frame)
output_image = draw_bbox(frame, bbox, label, conf)
cv2.imshow("Object Detection", output_image)
if cv2.waitKey(1) & 0xFF == ord("q"):
break
Here is a demo video:
Cisco Meraki Ecosystem Partners
If you want to explore a ready-made AI/ML solution from Cisco Meraki Ecosystem partners focusing on MV cameras, go to Meraki Marketplace.
Related resources
- Coding Tutorial: Object Detection using OpenCV Python in 15 Minutes!
- Download yolo config and weights
- Source Code
- Article: How to Implement Object Detection Using Deep Learning: A Step-by-Step Guide
