15 Jun · 5 min read
The ways of processing data are constantly evolving. Earlier, while it would take several minutes to process big data, this duration is barely noticeable today. We no longer have to think about delays from data processing.
Yet, the advancements have started a new race for the most efficient way to process data, especially for images and videos. With real-time, near-real-time, and batch processing options, it all boils down to your priorities and tools.
This article explores real-time and near-real-time image and video processing, their applications, challenges, and the best way to implement them.
Real-time processing requires a continuous inflow of data to process and provide a steady output. It is often seen in scenarios where immediate processing is critical, such as customer care systems and ATMs.
Near-real-time processing is preferred when the processing time is longer, but the output needs to be quick. This is often used in scenarios where the data sets are significant but need to be critically processed, such as intruder detection in networks or generating leads in sales.
Artificial Intelligence (AI) and machine learning (ML) can speed up data processing and improve quality. The use of AI platforms can be helpful in object detection, facial recognition, and recognition of text and images. ML algorithms can interpret the image and video data in the same manner that our brains do. AI and ML are often used to pictures on our smartphones and to automate self-driving automobiles.[Text Wrapping Break]AI and ML can play a significant role in video processing projects as they have a lot of benefits, as follows:
DAC.digital, has recently used AI and Computer Vision in several image and video-processing projects. When one of their clients came to them with the requirement of a ￼football-tracking app, they followed a DevOps methodology to create a high-tech mobile app. Expert DAC.digital developers carried out the work in an independent and interdisciplinary team. The primary areas of their involvement relied on their experience with Data Science with Python, Image Analysis expertise, and DevOps support.
The image/video processing industry is relatively new yet significantly in demand. While hiring is already pretty tough, looking for talent in this niche skillset makes this even harder.
Most real-time and near-real-time data processing requirements are used in time- and security-critical applications or software. So, it is crucial to have at least 2-3 experts on the topic.
But, as this skill set is highly sought after, the best in the business are already employed with the leading companies. Also, it can be pretty expensive to hire a full-time expert for just one project or feature build.
The above are crucial reasons many companies choose to outsource image/video processing projects.
As mentioned above, you need a team of experts to handle projects like these. Thousands of software companies worldwide take on short-term and long-term projects for clients just like you. Many of these vendors have expertise in specific industries and technologies that might be precisely what you’re looking for. Hiring such vendors for the short-term eliminates the hassle of hiring an in-house team and reduces your costs. While an in-house team can cost you the salaries of multiple employees over multiple months, you only pay for the project's duration during outsourcing.
Outsourcing also helps reduce project planning and management struggles, as the right partner is already aware of the complexities of the project and can help you plan more effectively.
DAC.Digital, are a team of engineers and problem solvers with expertise in various technologies and industries, especially in deep-tech and emerging-tech. Feel free to reach out to them for your next project.