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How can image processing improve safety in control systems?

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Image processing is the technique of manipulating and analyzing digital images to extract useful information or enhance their quality. It has many applications in various fields, such as medicine, astronomy, robotics, and security. But did you know that image processing can also improve safety in control systems? Control systems are systems that use sensors, actuators, and feedback loops to regulate the behavior of a physical process or a device. For example, a thermostat is a control system that adjusts the temperature of a room based on the input from a sensor. In this article, we will explore how image processing can help control systems achieve better performance, reliability, and security.

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Ahmad Yarahmadi

Assistant Professor at Ayatollah Borujerdi University | Lecturer & Researcher
Steve Lascos

Principal Engineer at Untether AI
Shelley Zhang

Engineer/Scientist | Minimally Invasive Surgery

1 What is image processing?

Image processing is the process of transforming an image into another image or a set of data that represents some features or properties of the original image. Image processing can be done in different ways, such as filtering, segmentation, edge detection, compression, enhancement, restoration, and recognition. Image processing can be applied to different types of images, such as grayscale, color, binary, or multidimensional images. Image processing can be performed using software, hardware, or a combination of both.

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Ahmad Yarahmadi

Assistant Professor at Ayatollah Borujerdi University | Lecturer & Researcher
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Image processing enhances safety in control systems by enabling real-time surveillance, anomaly detection, and emergency response. It monitors equipment, detects defects, and predicts maintenance needs. Image analysis aids in detecting fire, smoke, and intruders, ensuring immediate alerts and responses. In occupational settings, it ensures proper safety gear usage and monitors worker postures. Additionally, image processing is vital in environmental monitoring, traffic safety, and security systems, identifying hazards, managing traffic flow, and controlling access to secure areas. Integrating these technologies improves overall safety, prevents accidents, and facilitates rapid responses in emergencies.

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Shelley Zhang

Engineer/Scientist | Minimally Invasive Surgery
(已编辑)
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Think of us while driving, we process the scenes through our eyes before taking action to avoid potential collisions. Similarly, image processing equipped in the device systems can trigger safety flags and guide action plans, as below: 1. Object: The most common application is object detection. By recognizing the object, the control system can make decisions, e.g. to stop. 2. Location: By precisely detecting the location and/or orientation of the target of interest, the control system can take safety controls, e.g. to alter the trajectory. 3. Depth: This aspect is extended from stereo vision, where, the distance of the potential target can be estimated so that the control system can judge whether the danger is truly applicable.

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Haseeb Ur Rehman- MPM, BEE

Assistant Manager projects (PMO) | Expertise in Project & Engineering Management | Electrical Engineering |
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Image processing, a crucial component in modern control systems, can enhance safety through real-time analysis of visual data. By detecting anomalies, such as equipment malfunctions or security breaches, it enables timely responses to potential hazards. Additionally, image processing can augment autonomous systems, ensuring safer operation in various applications. It plays a pivotal role in object recognition, tracking, and monitoring, contributing to safer and more efficient control systems across industries. In summary, image processing leverages visual information to proactively identify safety concerns and support informed decision-making in control systems.

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2 Why use image processing in control systems?

Image processing can provide several benefits for control systems, such as improving the accuracy and quality of sensor data by reducing noise, correcting distortions, and extracting relevant information. It can also enhance the visualization and monitoring of the system by generating high-resolution, clear, and informative images. Additionally, image processing can increase the security and robustness of the system by detecting and preventing attacks, faults, or anomalies that could compromise safety or functionality. For instance, it can identify unauthorized intrusions, tampering, or sabotage as well as verify user identity and authorization of commands.

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Steve Lascos

Principal Engineer at Untether AI
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Human vision provides the most information to the brain of all our senses. Unfortunately, intensive focus on processing all this information for long periods of time quickly fatigues the brain. Image processing excels at handling the fatiguing parts and maintains performance and consistency. Raising alarms or flagging a human to interpret detected situations allows them to step in and apply their superior skills of deductive reasoning to effectively interpret and take action.

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Qudus Ajiboye

Engineering Solutions | IT Versatility | Project Management | Expertise in Process Optimization & Smart Homes Automation
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It can be used in detecting and identifying potential threats in the environment, such as fire, smoke, gas leaks, intruders, etc. For example, algorithms can be trained on a baseline of common patterns, and software can provide unparalleled threat detection capacity.

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3 How to implement image processing in control systems?

Image processing can be implemented in control systems using different methods and tools, depending on the requirements and specifications of the system. Generally, it involves image acquisition, preprocessing, analysis, processing, and output. Image acquisition is the process of capturing images from sensors or other sources, such as cameras, radars, or lidars. Image preprocessing prepares the images for further processing, such as filtering or resizing. Image analysis extracts information or features from the images, like edges or contours. Image processing transforms the images or extracted information into another image or data set that serves the purpose of the control system. Finally, image output is the process of displaying, storing, transmitting, or using the images or data for the control system. All these steps help to complete the image processing cycle and achieve the intended function of the control system.

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4 What are some examples of image processing in control systems?

Image processing can be applied to various types of control systems, such as industrial control systems, autonomous control systems, and biomedical control systems. In industrial control systems, image processing can help measure, monitor, and optimize the quality, efficiency, and safety of the production or service by detecting defects, errors, or deviations. For autonomous control systems, image processing can enable obstacle avoidance, path planning, target tracking, or face recognition for autonomous agents. In biomedical control systems, image processing can enable image-guided surgery, drug delivery, or prosthetic control for biomedical applications. This technology can thus help to ensure the smooth operation of machines and processes in industries and the navigation and adaptation of autonomous agents in their environment.

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5 What are some challenges and limitations of image processing in control systems?

Image processing in control systems can also face some challenges and limitations, such as computational complexity and cost due to the need for a large amount of computing power, memory, and bandwidth to process high-dimensional data in real time or near real time. This can increase the complexity and cost of the hardware and software of the control system, as well as affect its scalability and reliability. Furthermore, data quality and availability can be affected by noise, blur, distortion, occlusion, sensor failure, interference, or attack. Additionally, ethical and legal issues can arise from capturing, processing, or sharing sensitive or personal information from images like faces, identities, or activities. This can create risks or challenges for the protection and regulation of the data and the rights of the individuals or entities involved.

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Steve Lascos

Principal Engineer at Untether AI
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Most image processing systems tend to be monocular (non-stereo) and thus do not have depth information. Combining this with a lack of context means it is difficult for image processing to be a true replacement for human operators. AI can help bridge this gap by making image processing and computer vision closer to the performance of a skilled human.

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6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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How can image processing improve safety in control systems?

1

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5

6

1 What is image processing?

2 Why use image processing in control systems?

3 How to implement image processing in control systems?

4 What are some examples of image processing in control systems?

5 What are some challenges and limitations of image processing in control systems?

6 Here’s what else to consider

Electrical Engineering

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How can image processing improve safety in control systems?

1

2

3

4

5

6

1 What is image processing?

2 Why use image processing in control systems?

3 How to implement image processing in control systems?

4 What are some examples of image processing in control systems?

5 What are some challenges and limitations of image processing in control systems?

6 Here’s what else to consider

Electrical Engineering

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