Artificial intelligence security monitoring technology is spreading to a wider range of countries at a faster speed. At least 75 of the 176 countries in the world are actively using AI for surveillance purposes, which include: smart city / Safe City platform (56 countries), facial recognition system (64 countries), and smart Policing (52 countries).
AI is Playing an Increasingly Important Role
AI has a great influence because it has the function of self-learning.
More info: How machine learning works?
Initially, computers learned to “infer” objects of interest in a scene. Now, it can detect objects in the real world, and match the results with the labeled data (provided by humans), and then try to improve the result further. In each stage, the error rate will be smaller and finally lower than human error.
There are some key applications of AI in the surveillance scenes, such as object/person tracking, area monitoring, parking occupancy detection, vehicle analysis, and traffic monitoring. Especially during the global covid-19 crisis, many companies have spent a lot of energy to build Ai based systems to ensure social isolation in public areas.
AI is everywhere.
For example, for personnel tracking, video processing is completed in real-time, which is used to analyze and identify security risks that may pose risks to enterprises. Video analysis technology effectively enables monitoring software to infer and detect abnormal behavior, and identify potential safety situations that may be ignored by humans.
More info: Labeling Service Case Study — Video Annotation — Vehicle License Plate Recognition
As a strong demand, security is the most important scene for AI landing and has become a competitive place.
AI Security Scenarios
- Facial Recognition
- Video Surveillance Development
- Precise Gesture Recognition&Identification
- Vehicle &Traffic Objects Detection: License plate information, vehicle color, car model,
- Street Scene Segmentation
- Traffic Light Detection
- Threat Detection
A lot of sensitive data, such as face data, license plate data, and so on, would be frequently exposing. Therefore, the storage and transmission of the data require a high level of security
Different countries have issued corresponding laws and regulations for data security. For example, according to the EU GDPR, data cannot leave the EU region.
Another security concern is a data leak. Once data transmitted, it is possible to get copied. Customers are worried that the data will be directly copied and sold to competitors.
In conclusion, except for legal norms, data security is essentially a matter of trust.
The strength of an AI system mainly depends on two things:
1. The quality of the algorithm model
2. The quantity and quality of training data
Now many companies in the field of AI are using similar algorithms, many even are using the same open-source project.
In other words, the amount of data and the quality of the data used in algorism training can play a decisive role.
In addition to visual recognition, there is also a huge need for data collection and labeling in areas such as speech recognition and text recognition.
Data Labeling Tools in Securities
Video Tracking, Point Annotation,2D Bounding Box
More info:8 Common Data Annotation and Labeling Tools
ByteBridge, a human-powered and ML-powered data labeling tooling platform with real-time workflow management, providing high-quality data with efficiency.
Accuracy and Efficiency
- ML-assisted capacity can help reduce human errors by automatically pre-labeling
- The real-time QA and QC are integrated into the labeling workflow as the consensus mechanism is introduced to ensure accuracy
- Consensus — Assign the same task to several workers, and the correct answer is the one that comes back from the majority output
- All work results are completely screened and inspected by the machine and human workforce
- In this way, ByteBridge can affirm our data acceptance and accuracy rate is over 98%
We comply with principles and rules in each region and we respect data the way your company does.
- The CEO of the company supervises data management as a DPO (Data Protection Officer)
- According to the guideline, if there is data leakage, we will inform the customer within 72 hours
- GDPR personal privacy and data protection regulations compliance
- Workers location, process, and authority restriction
- No original data leak as the data is compressed and preprocessed
- Support private cloud and privatization deployment
- ISO27001 certification for information and facility security
A collaboration of the human-work force and AI algorithms ensure a 50% lower price compared to the conventional market.
If you need data labeling and collection services, please have a look at bytebridge.io, the clear pricing is available.
Please feel free to contact us: firstname.lastname@example.org