Synthetic Intelligence (AI) on the edge is in style amongst good video gadgets. For instance, Good Dwelling cameras and video doorbells revolutionized house monitoring. What started as easy recording and distant viewing instruments has developed into clever observers. With AI infusion, at present’s cameras can actively analyze scenes, alert customers to movement occasions, acknowledge acquainted faces, spot package deal deliveries, and dynamically alter their recording habits. Enterprise surveillance cameras are one other instance. These cameras have superior decision, enhanced computing energy, and might drive extra subtle AI fashions. These enhanced capabilities lead to sharper detection at better distances.
As illustrated, clients demand clever monitoring programs that may course of information regionally whereas sustaining privateness and decreasing bandwidth prices. To deal with these wants, the AWS Web of Issues (AWS IoT) workforce has developed a sensible digital camera resolution with AWS companions that mixes Amazon Kinesis Video Streams, Realtek’s low-power Ameba Pro2 microcontroller, and environment friendly machine studying fashions from Plumerai. This weblog publish offers steering for event-triggered video uploads coupled with human detection algorithm processing on the edge.
Resolution structure
Determine under illustrates the answer structure that this weblog makes use of:

- Starting with the digital camera, the machine firmware has built-in Realtek SDK to entry digital camera modules by way of outlined APIs.
- The video fragments are delivered to Plumerai’s machine studying fashions for object detection.
- The pattern utility provides detection outcomes as bonding field overlay on the unique video fragments. This pattern constantly uploads the fragments to cloud by way of Kinesis Video Streams Producer SDK. (As an apart, you can even set detection outcomes to set off uploads of 20-second video segments.)
- The Kinesis Video Streams Producer SDK depends on PutMedia API with lengthy HTTPS connection to add MKV fragments constantly in a streaming means.
- The media information will probably be ingested and the service shops all media information persistently for later evaluation.
- A frontend utility performs the playback of stay, or beforehand recorded movies, counting on HLS or DASH protocols from Kinesis Video Streams.
- The answer feeds video and audio information into Giant Language Fashions (LLMs) for Agentic AI insights. (We are going to cowl semantic video search in our subsequent weblog).
Integration highlights
Amazon Kinesis Video Streams
Kinesis Video Streams transforms how companies deal with video options for IP cameras, robots, and cars. Key advantages embrace:
- A completely managed structure. This helps engineering groups deal with innovation as a substitute of infrastructure and is good for corporations with restricted sources.
- AWS SDKs are open-sourced. Prime manufacturers particularly worth this independence from platform constraints.
- Versatile pay-per-use pricing mannequin. Whereas machine improvement can take months or years, you don’t pay till the cameras go stay. With typical cloud storage activation under 30% and declining yearly utilization, prices keep dramatically decrease than mounted license charges.
Plumerai
The Plumerai firm makes a speciality of embedded AI options, specifically targeted towards making deep studying tiny and environment friendly. The Plumerai mannequin helps to supply inference on small, reasonably priced, and low-power {hardware}. The corporate additionally optimizes AI fashions for the Realtek Ameba Pro2 platform by way of:
- Meeting-level optimizations can maximize Arm Cortex-M CPU efficiency, and leverages DSP directions for enhanced sign processing capabilities.
- Neural Structure Search (NAS) selects optimum AI fashions for Realtek NPU and reminiscence structure to attain 0.4 TOPS NPU acceleration
- Plumerai fashions use Realtek on-chip {hardware} accelerators (scalers, format converters) to scale back computational load.
- The AI mannequin helps RTOS to seamlessly integrates the SoC’s real-time working system.
- The appliance integrates with Realtek’s media streaming framework.
- The quick boot design helps speedy booting occasions, which improves battery life, and ensures excessive velocity of lively object detection.
- The sting AI fashions are educated on 30 million labeled photographs and movies.
These enhancements translate into the next real-world efficiency:
- Delivers precision with out losing reminiscence.
- Captures extensive scenes by way of 180° field-of-view lenses.
- Detects people at 20m+ (65ft) distances.
- Handles crowds by monitoring 20 individuals concurrently.
- Maintains particular person monitoring with a singular ID system.
- Performs constantly in brilliant daylight and complete darkness.
Realtek Ameba Pro2

Determine above illustrates Realtek Ameba Pro2’s information structure. It comprises Built-in Video Encoder (IVE) and an Picture Sign Processor (ISP) that processes media’s uncooked information and delivers the consequence to a Video Offload Engine (VOE). The VOE then manages a number of video channels and concurrent video streams to help the movement detection algorithm. The Neural Processing Unit (NPU) performs inference on photographs or picture areas. The Parallel Processing Unit (PPU) handles multitasking jobs like cropping Areas of Pursuits (ROIs) from high-resolution photographs, resizing NPU inference enter, and retrieving remaining output from high-resolution channels.This structure unlocks highly effective capabilities to help video analytics on the edge, together with:
- Runing with minimal CPU energy for max effectivity.
- Responding in close to actual time to movement.
- Start video processing even in the course of the boot sequence.
- Streaming to each the SD card and cloud by way of safe WiFi or Ethernet.
- Leveraging NPU to ship superior AI efficiency.
- Integrating with Plumerai fashions and Kinesis Video Streams by way of a multimedia framework SDK.
Walkthrough
This part outlines the constructing steps for the answer to run edge AI and stream the video fragments.
Stipulations
- AWS account with permission for:
- A stream useful resource with the identify “kvs-plumerai-realtek-stream” created on Kinesis Video Streams Console.
- The Realtek Ameba Pro2 Mini MCU.
- Primary information about embedded programs and dealing in a Linux surroundings.
- Web connection to obtain the SDK and add movies to AWS.
- Library and machine studying mannequin information from Plumerai. (Please submit your request on the Plumerai Web site.)
Arrange the constructing surroundings
This weblog makes use of an Amazon EC2 with Ubuntu LTS 22.04 because the constructing surroundings. You need to use your individual Ubuntu pc to cross-compile the SDK.
Amazon EC2 occasion setup:
- Register into the AWS administration console and navigate to Amazon EC2.
- Launch an occasion with the next configuration:
- Occasion identify: KVS_AmebaPlumerAI_poc
- Utility and OS Photographs: Ubuntu Server 22.04 LTS (HVM)
- Occasion sort: t3.giant
- Create a brand new key pair for login: kvs-plumerai-realtek-keypair
- Configure storage: 100GiB
- Observe SSH connection conditions to permit inbound SSH site visitors.
Obtain pattern script from Github:
- Utilizing the next command, log into your Amazon EC2 occasion (you’ll want to substitute xxx.yyy.zzz with the occasion’s IP tackle). For detailed directions, see Connect with your Linux occasion utilizing an SSH shopper.
Acquire the Plumerai library:
- Utilizing the Plumerai contact us type, submit a request to obtain a replica of their demo package deal. After getting the package deal, substitute the “plumerai” listing with it within the Amazon EC2 occasion. The up to date listing construction ought to be the next:

Acquire the Ameba SDK:
- Please contact Realtek to acquire the most recent Ameba Pro2 SDK. Within the listing construction, substitute the “ambpro2_sdk” in Amazon EC2. The listing construction ought to be the next:

Set up dependencies and configure surroundings
- Run the script setup_kvs_ameba_plumerai.sh within the listing sample-kvs-edge_ai-video-streaming-solution from the Github repository:
The script will mechanically set up the Linux dependencies, construct the Realtek toolchain, run mandatory Plumerai patches, copy mannequin information, and obtain the Kinesis Video Streams Producer SDK. If you happen to expertise an error within the course of, please contact Realtek or Plumerai for technical help.
Configure pattern in Kinesis Video Streams Producer SDK
Use the next to configure AWS credentials, stream identify, and AWS area. These may be discovered within the part/instance/kvs_producer_mmf/sample_config.h file.
Remark out example_kvs_producer_mmf(); and example_kvs_producer_with_object_detection(); within the file /house/ubuntu/KVS_Ameba_Plumerai/ambpro2_sdk/part/instance/kvs_producer_mmf/app_example.c






Zihang Huang is an answer architect at AWS. He’s an IoT area skilled for linked automobiles, good house, good renewable power, and industrial IoT. Earlier than AWS, he gained technical expertise at Bosch and Alibaba Cloud. At present, he focuses on interdisciplinary options to combine AWS IoT, edge computing, large information, AI, and machine studying.
Siva Somasundaram is a senior engineer at AWS and builds embedded SDK and server-side parts for Kinesis Video Streams. With over 15 years of expertise in video streaming providers, he has developed media processing pipelines, transcoding and security measures for large-scale video ingestion. His experience spans throughout video compression, WebRTC, RTSP, and video AI. He’s obsessed with creating metadata hubs that energy semantic search, RAG experiences, and pushing the boundaries of what’s potential in video expertise.
Emily Chou is director at Realtek Semiconductor Corp. She makes a speciality of wi-fi communication community expertise and has labored with a number of generations of the AmebaIoT MCU. She guides a workforce to supply connectivity options, video analytics, and edge AI computing.
Marco Jacobs is the Head of Product Advertising at Plumerai, the place he drives adoption of tiny, extremely correct AI options for good house cameras and IoT gadgets. With 25 years of expertise in digital camera and imaging purposes, he seamlessly connects executives and engineers to drive innovation. Holding seven issued patents, Marco is obsessed with remodeling cutting-edge AI expertise into enterprise alternatives that ship real-world influence.