Using Object Detection on IoT Devices

Something big is happening! The real world is being radically transformed by tech. Forward-thinking businesses are focusing to make the most significant change since the invention of the printed circuit board.

Artificial intelligence (AI) is here. Consumers use it every day to shop, get directions and search on the internet. Devices are getting smarter and more connected across industries, including consumer electronics, manufacturing, healthcare, transportation, and more.

AI will eventually affect many more areas and one key segment of this shift is being powered by computer vision (CV). CV is the part of AI that enables computers to analyze visual data and make decisions based on what they “see.” New technologies such as the Internet of Things (IoT) and 5G are creating fantastic new uses. Whether you’re working with a connected IoT device or an unconnected embedded device on the edge, the ability to build and train machine learning AI in your app is more accessible than ever before.

One of the cornerstones of computer vision is object detection. It's an excellent place to explore some of the fascinating things that AI brings to everyday life.

Life on the High-Speed Edge

Object detection decides if an object is present in an image or not. It determines where in the frame it’s located. The algorithm used to accomplish this task is relatively simple, but it produces powerful results. In the IoT schema, sensors collect data. It's more efficient to process this constant stream of data (i.e., from a video camera) on the sensors rather than transport data across the network or onto the cloud. 

Cameras perform object detection and related tasks like object counting and classification. Doing this preprocessing work on the device increases efficiency by keeping unnecessary traffic off the network.

Examples of Object Detection

Applications

The AI space is changing as developers are now aware of the potential of the tools  available. Here are some uses of object detection, and other computer vision services:

• Healthcare. Since most medical data is visual, object detection is a natural fit. Using computer vision in the healthcare field for analyzing X-rays and other forms of imaging is already helping healthcare professionals provide appropriate treatment plans. Procedures such as endoscopies allow cameras to identify certain classes of malignant cells instead of relying solely on the physician’s human eye.
  
  
• Security. Protection against crime and terrorism are at the forefront of object detection. Spotting out-of-place packages in airport or tracking suspects is just the beginning of the uses of object detection for security reasons.
  
  
• Agriculture. Farmers use object detection to identify pests in their crops. In fact, the ability to target only the pests can reduce (and perhaps, eliminate) the use of herbicides and pesticides.
  
  
• Manufacturing. Detecting objects in images improve manufacturing tasks such as counting, sorting and quality control. AI contributes to productivity by helping manufacturers with predictive maintenance and plant automation.
  
  
• Industrial. Operators of remote storage facilities for petroleum and chemicals benefit from object detection systems that report leaks, spills or other problems in real-time. 
  
  
• Smart Cities. Cities in the future will incorporate all forms of AI to provide a better living environment for their citizens. Object detection will play a critical role by providing a means to regulate traffic flow, provide protection against criminal activity, and help improve sanitation by identifying problem areas.

Object Detection Is Changing the World as We Know It

The world is just starting to experience some of the benefits of AI and CV. For example, healthcare is already using some amazing applications that will improve the quality of life and potentially save countless lives. The potential of these technologies are unlimited. This bring new opportunities to developers around the world. The future of CV and AI is bright, and the impact of these technologies will reach billions of end-users sooner than expected.