When iB3 started in 2014 we had a major focus on “Biometry” and “Face Recognition”, the imaging solution we developed was based on ML (Machine learning) techniques.
4.1) Imaging
Early 2000, a team of professors and researchers operating in the Image Processing domain became operational in developing the original implementation of the Face Recognition Biometrics Algorithms whose evolution is actually used in iB3.
In 2004 a full immersion of the research was well established. The main endeavors were focused on conducting in depth assessments of this discipline.
By 2007 renewed direction in the development of the study of Facial Biometrics. These experiences added to the value of complete project integration and experience.
Since 2011 iB3 engineers have teamed up with MPXLab (no-profit research organization located in Italy) in order to develop next generation video analytics
In 2018 SophyAI was conceived
4.2) IoT
According to Gartner, the Internet of Things (IoT) market is projected to nearly double, growing from $546 billion in 2022 to $991 billion by 2028. This substantial growth reflects the increasing adoption of IoT devices across various industries.
In the realm of video surveillance, significant advancements are anticipated by 2025. The industry is poised to enter an era of super-intelligent video surveillance, moving beyond basic detection and search capabilities toward autonomous decision-making based on comprehensive understanding and analysis. Artificial intelligence (AI) continues to redefine what’s possible in video surveillance, with edge AI driving this transformation. This evolution enables more proactive and intelligent security measures, such as real-time anomaly detection and predictive analytics.
The integration of IoT devices and AI in video surveillance systems enhances operational efficiency and customer service. Advanced video analytics facilitate applications like people counting, dwell time analysis, and object recognition, providing businesses with real-time insights into their operations. This data-driven approach allows for better resource allocation and improved decision-making.
Moreover, the adoption of cloud-based video surveillance solutions is on the rise, offering scalability and remote accessibility. Cloud technology unlocks the full potential of data utilization, enabling seamless integration with other systems and facilitating more efficient data management. This shift toward cloud solutions supports the growing demand for interconnected and intelligent surveillance infrastructures.
In summary, the convergence of AI, IoT, and cloud technologies is driving the evolution of video surveillance systems. These advancements are leading to more intelligent, efficient, and proactive security solutions that not only enhance safety but also provide valuable operational insights for businesses.