In this article, I will expand on one of my early posts. Much popular technology, security industry blogs, and manufacturers websites talk about AI extensively. Some, excellent in technical details, while others confuse terminology, adding misunderstanding to the subject.
I will explore bellow themes:
1. terminology
2. current applications
3. examples of functional features
I will not dive into ethics as it is a complex subject. However, It is essential to add that there are far too many issues. An AI expansion will propel economic growth and significantly advance most sectors. We must ask privacy and ethics questions and build controls to eliminate the associated risks.
Note: China is a primary driver of AI surveillance worldwide. Chinese product pitches are often accompanied by soft loans to encourage governments to purchase their equipment.
Lack of regulations is a thin line between lawful and unlawful surveillance, posing risks with these fast-expanding technologies. For example, new boundaries, accountability, issues around digital repression, privacy by design and privacy by default.
1. TERMINOLOGY
Artificial Intelligence (AI), for example, IBM Deep Blue
Alan Turing’s definition would have fallen under the category of “systems that act like humans.”
Artificial intelligence is a field, which combines computer science and robust datasets to enable problem-solving. It also encompasses sub-fields of machine learning and deep learning, which are frequently mentioned in conjunction with artificial intelligence. These disciplines are comprised of AI algorithms that seek to create expert systems that make predictions or classifications based on input data.
Machine Learning (ML), for example, IBM Watson
The subfield of the AI whereby deep learning is the subfield of Machine Learning, see above.
Deep Learning (DL), Google Alpha Go
Deep learning is comprised of neural networks. “Deep” in deep learning refers to a neural network comprised of more than three layers—which would be inclusive of the inputs and the output—which can be considered a deep learning algorithm.
2. APPLICATIONS
Facial Recognition Technologies (FRT)
A biometric technology that uses cameras—both video or still images—to match
stored or live footage of individuals with images from a database. Not all facial recognition systems focus on individual identification via database matching. Some systems are designed to assess aggregate demographic trends or conduct broader sentiment analysis via facial recognition crowd scanning. Facial recognition systems are rapidly spreading around the world. Many countries are actively incorporating facial recognition systems in their AI surveillance programs. Advanced video surveillance and facial recognition cameras could not function without cloud computing capabilities.
Automated Border Control Systems
Primarily in international airports and border crossings. For example, the controversial and widely criticised project is The European Union iBorderCtrlto that screen migrants at border crossings. Individuals are asked questions about their countries of origin and circumstances of departure. An AI-based lie-detecting system then evaluates the answers.
Crowd Control
Saudi Arabia’s Makkah Region Development Authority (MRDA) created a crowd-control
system to increase the safety and security of Hajj pilgrims. Data is collected via a wristband
embedding identity information, special healthcare requirements and a GPS. In addition,
surveillance cameras are installed to collect and analyse real-time video along with the Al.
Smart City
In Serbia, Huawei’s safe city project installed 1,000 high-definition (HD) cameras with facial recognition and license plate recognition capabilities in 800 locations across Belgrade. Important to add that this sparked national outrage due to privacy issues as well as government opposition repression.
3. FUNCTIONAL FEATURES
· ML is employed to monitor a vast amount of video streams and never tire or fatigue.
· Automatic license plate recognition ML to recognise license plates from different countries.
· ML-based solutions in a Video Management System where video presents a vast amount of complex, unstructured information.
Are you looking to improve your surveillance?Here at Jansta Associates Limited, we serve our clients with a vast array of engineering consulting services. So, if you are thinking of deploying a new technology or design or updating existing surveillance systems, we can help you navigate this complex subject. Want to find out more? Get in touch today.
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