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AWS IoT Core VS OpenCV

Compare AWS IoT Core VS OpenCV and see what are their differences

AWS IoT Core logo AWS IoT Core

Whether building a connected home application for home security or building an industrial application to proactively identify equipment breakdown, you can use AWS IoT Core to securely communicate with and gather data from your diverse fleet of IoT d…

OpenCV logo OpenCV

OpenCV is the world's biggest computer vision library
  • AWS IoT Core Landing page
    Landing page //
    2022-02-05
  • OpenCV Landing page
    Landing page //
    2023-07-29

AWS IoT Core videos

Getting Started with AWS IoT Core for LoRaWAN

More videos:

  • Review - How can I start publishing messages to AWS IoT Core from my device?

OpenCV videos

AI Courses by OpenCV.org

More videos:

  • Review - Practical Python and OpenCV

Category Popularity

0-100% (relative to AWS IoT Core and OpenCV)
Data Dashboard
100 100%
0% 0
Data Science And Machine Learning
IoT Platform
100 100%
0% 0
Data Science Tools
0 0%
100% 100

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare AWS IoT Core and OpenCV

AWS IoT Core Reviews

Open Source Internet of Things (IoT) Platforms
It is a managed cloud service. AWS IoT Core will allow devices to connect with the cloud and interact with the other devices and cloud applications. It provides support for HTTP, lightweight communication protocol, and MQTT.
14 of the Best IoT Platforms to Watch in 2021
AWS IoT Core is a behemoth in IoT platforms, and is the backbone of many fascinating projects such as Expedia, AirBnB, and CoinBase. With support for device software such as FreeRTOS and AWS IoT Greengrass, AWS IoT Core encompasses a vastly superior ecosystem of products allowing development in smart homes and industrial automation. All AWS data is visualized on an AWS IoT...

OpenCV Reviews

7 Best Computer Vision Development Libraries in 2024
From the widespread adoption of OpenCV with its extensive algorithmic support to TensorFlow's role in machine learning-driven applications, these libraries play a vital role in real-world applications such as object detection, facial recognition, and image segmentation.
10 Python Libraries for Computer Vision
OpenCV is the go-to library for computer vision tasks. It boasts a vast collection of algorithms and functions that facilitate tasks such as image and video processing, feature extraction, object detection, and more. Its simple interface, extensive documentation, and compatibility with various platforms make it a preferred choice for both beginners and experts in the field.
Source: clouddevs.com
Top 8 Alternatives to OpenCV for Computer Vision and Image Processing
OpenCV is an open-source computer vision and machine learning software library that was first released in 2000. It was initially developed by Intel, and now it is maintained by the OpenCV Foundation. OpenCV provides a set of tools and software development kits (SDKs) that help developers create computer vision applications. It is written in C++, but it supports several...
Source: www.uubyte.com
Top 8 Image-Processing Python Libraries Used in Machine Learning
These are some of the most basic operations that can be performed with the OpenCV on an image. Apart from this, OpenCV can perform operations such as Image Segmentation, Face Detection, Object Detection, 3-D reconstruction, feature extraction as well.
Source: neptune.ai
5 Ultimate Python Libraries for Image Processing
Pillow is an image processing library for Python derived from the PIL or the Python Imaging Library. Although it is not as powerful and fast as openCV it can be used for simple image manipulation works like cropping, resizing, rotating and greyscaling the image. Another benefit is that it can be used without NumPy and Matplotlib.

Social recommendations and mentions

Based on our record, OpenCV should be more popular than AWS IoT Core. It has been mentiond 51 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

AWS IoT Core mentions (8)

  • WebSockets, gRPC, MQTT, and SSE - Which Real-Time Notification Method Is For You?
    MQTT - AWS IoT Core offers a managed MQTT message broker, giving you easy access to your devices. Fun fact, this is what powers the notifications in Serverlesspresso. - Source: dev.to / 8 months ago
  • Serverless Facial Recognition Voting Application Using AWS Services
    AWS IoT: For real-time communication between the server and the frontend application. - Source: dev.to / about 1 year ago
  • Building Serverlesspresso
    AWS IoT Core is a service that allows you to connect your devices securely to the AWS cloud and with ease. Option for device management, data processing as well as integration with other AWS services is provided. Click here for more on AWS IoT Core. - Source: dev.to / about 1 year ago
  • Use EventBridge to handle API requests
    From here you can do all sorts of actions. For example, the serverless-coffee project used IOT Core. With IOT Core you can notify the end-user with status updates. And notify the barista that what kind of coffee needs to be created. - Source: dev.to / over 1 year ago
  • API Gateway Websockets vs IoT Core
    When you need websockets in a project on AWS most likely API Gateway Websockets (I will refer to it as API Gateway from now on) is the first service coming to mind. At some point when looking into options, I ran into IoT Core instead. I thought this was meant only for very specific scenarios involving hardware; however it also supports MQTT over websockets which makes it an amazing choice for web and app. I think... - Source: dev.to / over 1 year ago
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OpenCV mentions (51)

  • FridgeBot — GPT-4o shopping list automation
    Open the camera feed — and use the OpenCV library for real-time computer vision processing. - Source: dev.to / 25 days ago
  • Exploring Open-Source Alternatives to Landing AI for Robust MLOps
    Data analysis involves scrutinizing datasets for class imbalances or protected features and understanding their correlations and representations. A classical tool like pandas would be my obvious choice for most of the analysis, and I would use OpenCV or Scikit-Image for image-related tasks. - Source: dev.to / 6 months ago
  • Looking for a Windows auto-clicker with conditions
    You might be able to achieve this with scripting tools like AutoHotkey or Python with libraries for GUI automation and image recognition (e.g., PyAutoGUI https://pyautogui.readthedocs.io/en/latest/, OpenCV https://opencv.org/). Source: 6 months ago
  • Looking to recreate a cool AI assistant project with free tools
    - [ OpenCV](https://opencv.org/) instead of YoloV8 for computer vision and object detection. Source: 11 months ago
  • Looking to recreate a cool AI assistant project with free tools
    I came across a very interesting [project]( (4) Mckay Wrigley on Twitter: "My goal is to (hopefully!) add my house to the dataset over time so that I have an indoor assistant with knowledge of my surroundings. It’s basically just a slow process of building a good enough dataset. I hacked this together for 2 reasons: 1) It was fun, and I wanted to…" / X ) made by Mckay Wrigley and I was wondering what's the easiest... Source: 11 months ago
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What are some alternatives?

When comparing AWS IoT Core and OpenCV, you can also consider the following products

AWS IoT - Easily and securely connect devices to the cloud.

Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.

ThingSpeak - Open source data platform for the Internet of Things. ThingSpeak Features

Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.

Blynk.io - We make internet of things simple

NumPy - NumPy is the fundamental package for scientific computing with Python