Computer Vision trends that will dominate the industry in 2021
During the current pandemic, the one thing which every brand adopted is a quick digital transformation. The transformation which would have taken place in the next 5 years, just happened in the past six months. This accelerated adoption will continue in 2021 in the areas of intelligent industrial automation and artificial intelligence.
Video analytics powered by computer vision will revolutionize risk management and mitigation, automated monitoring, and security, which will achieve operational efficiency in industrial environments. Keeping the prospects of growth in mind, amalgamation, or advanced computer vision with different techs will dominate the year 2021.
Here are the Top 6 Computer Vision Trends that will dominate the industry in 2021
- Make way for safety: Ensure public and workplace safety
Ensuring safety in every organization is very important. Therefore, safety protocols and new daily routines have been introduced for improving the safety programs approach. Currently, technology is playing a significant role in facilitating those enforced changes. And vision intelligence is further being utilized by many industries around the globe for implementing safety.
HSE video anomaly detectors have been proven effective for automated monitoring and analysis for finding anomalies like absence of Safety Masks, PPE Kits, and other regulations like social distancing for employee safety.
2. Root for Quality Inspections: Automate Anomaly Detections
The largest electronic manufacturers have adopted the technologies for automating production monitoring and defect detection. High-quality images are produced; printed circuit boards are utilized for checking 20+ anomalies and defects.
Other industries like Automotive, Food and Beverage, and steel are leveraging computer vision for optimizing visual inspection and automation.
With a laid-off workforce and declining profit margins, 2021 would be the crucial year when more industrial leaders who are looking to utilize Computer Vision and AI inspections would gain golden quality, flexibility, accuracy and low cost, which the technology brings.
3. Opt for Non-destructive Testing: Utilization of Thermal Cameras
Augmented non-destructive testing computer vision is a solution which detects defects and marks the area of interest if there is a high probability for defined defects or anomalies, making use of radiology images that are taken via NDT techniques.
Automated Vision, which is based on inspections, widens the visible spectrum, and detects the metal surface defects which are often invisible to the human eye. Another fascinating applied thermal imaging data application is to recognize the surface cover of the Peruvian Andes glaciers, which shrunk by 30 % in the past few decades. Due to its melt rate, it’s a serious threat to the water supply for the people living in the Ancash region of Peru.
Advanced computer vision applications and deep learning technologies would further help in analysis and experiments in the upcoming years.
4. Gain in real-time: The advancement of Edge Computing
The rise of edge computing is quickly solving the problems of network accessibility and latency. This also helps in better real-time response and move with relevant insights to the cloud for further analysis.
It enables engineers, trainers, team leads, and quality teams of lining operators for examining every step of the manufacturing process with real-time video analytics. This saves a lot of time needed for manual cycle time monitoring and also optimizes the production cost.
5. Look for helping hands- Sensor Data Triangulation
Video Analytics is unleashing a new frontier for automating surveillance cases in the Military and Defense. The ability to detect events and alert the security has contributed to the physical security at national borders.
Advanced perimeter monitoring system gathers several forms of data such as video feeds, sensor data, and drone imagery from various touchpoints and triangulates them for providing real-time insights. This integration offers a multi-layered security system with robust features of unidentified object detection, intrusion detection, vehicle detection, and user access control.
6. Opportunity of Automation- The Closed Loop Solution
We have witnessed rigorous development in the last decade. And one simple example is automatic user access control by facial recognition.
The advancement of vision-based control is realized in the developments of autonomous cars and unmanned vehicles. Vision system controls the vehicle movements in real-time for any user-defined and desired inputs by making use of visual feedbacks only when conventional sources of accurate position or orientation data are not available.
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