Whether countertop surfing, unraveling toilet paper rolls, clawing furniture, knocking over houseplants or other innocent hijinks, monitoring your clever kitty’s mischievous behavior can help prevent destruction around your home. That’s why we set out to develop a smart cat detector using Amazon Kinesis Video Streams that can reliably detect cats and alert owners in real time when their feline friends are someplace they shouldn’t be.
With advanced video analytics powered by edge machine learning, even the slyest cat’s activities can be monitored 24/7. This case study addresses these playful shenanigans through a sophisticated IoT engineering application — a smart cat detector — that harnesses Amazon Kinesis Video Streams’ low-latency video ingestion and machine learning capabilities.
Even better, this project demonstrates the potential of Amazon Kinesis Video Streams in remote monitoring scenarios:
Our smart cat detector is an innovative IoT application that utilizes a trained machine learning model to detect the presence of cats in a given environment and alert owners in near real time. We utilized a model trained using the ImageNet dataset, a benchmark for computer vision research. When harnessing the power of machine learning, using pretrained models out of the box is much more common than wasting precious resources training your own model from scratch.
The cat detector project saw us implement an end-to-end pipeline, ingesting live video from a Raspberry Pi camera into Amazon Kinesis Video Streams. Kinesis Video Streams, or KVS, is a fully managed AWS video streaming service that enables secure video ingestion into the cloud. As a recognized AWS IoT Service Delivery partner, we specialize in harnessing KVS to create real-time video-enabled applications supporting live, recorded and two-way streaming.
Offering features such as indexing, video recognition, analysis and machine learning capabilities, Amazon Kinesis Video Streams is utilized to stream live video from devices to the AWS cloud or build applications for real-time video processing or batch-oriented video analytics.
Pet surveillance cameras — with KVS WebRTC, a managed P2P WebRTC streaming infrastructure — can provide real-time monitoring, streaming video data to AWS using KVS for secure storage and analysis. The video can be analyzed in real time to identify any unusual behaviors or incidents, enabling immediate response in case of emergencies.
Designed with built-in machine learning inferencing, our smart cat detector consists of two components — an IoT application running on the Pi and a website hosted in the cloud — to analyze video frames and identify cats, triggering alerts and audio feedback when you catch the culprit red-pawed.
KVS Cat Detector Components
Our smart cat detector is an AWS IoT Greengrass application that runs continuously on the Raspberry Pi as a set of background processes. The application includes the following components:
While robust edge analytics power real-time detection and response, our smart cat detector also leverages secure AWS cloud services to enable remote monitoring, scalable video ingestion and back-end integration.
Complementing the real-time edge capabilities, our smart cat detector system leverages several AWS cloud services intentionally designed for enhanced functionality and improved communication between the device and the cloud (using TLS).
To bolster security, we assigned permissions to the various system components following the principle of least privilege. With core detection driven by edge machine learning and video management handled via secure cloud infrastructure, our smart cat detector solution is primed for use in smart home environments.
During development, we experienced some issues with connecting KVS WebRTC to Amazon Kinesis Video Streams:
By writing a service running on AWS that joins the P2P KVS WebRTC mesh and either decimates and sends frames to AI/ML or stores video on Amazon S3, we worked around these concerns.
Other development challenges included the following:
But how does the smart cat detector work to alert you the moment your sneaky feline is causing trouble?
Cardinal Peak’s cat detector solution delivers a seamless experience for owners to monitor their pets and protect their belongings in just a few simple steps:
With our cat detector powered by Amazon Kinesis Video Streams, pet owners can enjoy peace of mind knowing their valuables are protected and our mischievous pets stay entertained without destructive consequences — even when we’re not home to intervene.
When left to their own devices, cats have a knack for keeping themselves entertained — often to the dismay of their owners. In our modern world, feline antics meet ingenious technology designed to keep a vigilant eye, offering peace of mind to pet owners everywhere.
The Amazon Kinesis Video Streams-powered cat detector system highlights the integration of IoT, machine learning and AWS services to address a unique need and real customer problems. Together, these technologies enable continuous cat monitoring with real-time response when furry felines wander into forbidden areas.
With machine learning models rapidly classifying incidents and Amazon IoT services, this smart cat detector project showcases Cardinal Peak’s expertise and talent in delivering inventive solutions harnessing AWS IoT Greengrass, machine learning and edge capabilities. Contact us to explore your custom Amazon Kinesis Video Streams solution with our team of IoT engineering and streaming video experts!