David Lee Of Scenera On The Future of The Internet of Things (IoT), And How It May Improve Our Health & Our Lives

by | Sep 11, 2023 | Press, News

CEO of Scenera, David D Lee

This article by David Leichner, CMO at Cybellum, was published via Authority Magazine on Sept 11, 2023. 

Embracing emerging technologies like generative AI or leveraging advanced AI processing capabilities at the edge is instrumental. By integrating and optimizing these new technologies and capabilities, businesses can generate superior business insights. This approach not only helps in winning over customers but also expands market reach.

The Artificial Intelligence of Things (AIoT) is beginning to become more mainstream with the combination of Artificial Intelligence (AI) technologies with the Internet of things (IoT) infrastructure to achieve more efficient IoT operations, improve human-machine interactions and enhance data management and analytics. Millions of people use Fitbit health trackers, Nest smart thermostats, and Ring doorbell cameras, which are early examples of IoT. These are just the tip of the iceberg when it comes to the potential commercial applications of AIoT. AIoT has the potential to change the way cities are run, the way our healthcare is managed, the way our cars communicate, and the way our supply chains and manufacturing are utilized. But how exactly will AIoT improve our lives? How can it improve our health? What are the new AIoT technologies that we should expect to see around the corner? How does one create a successful career in the AIoT industry? In this interview series, we are talking to business leaders who are incorporating AIoT into their business or who are developing AIoT applications, who can share stories and perspectives about the future of AIoT. As a part of this series, I had the pleasure of interviewing David Lee, CEO of Scenera.

David is a serial technology entrepreneur within the AI & IoT industry and is currently the Chief Executive Officer and Co-founder of Scenera Inc. Scenera is forging a new standard AI data analytics platform for the IoT industry by combining an open and flexible architecture with an intelligent platform. The result is an efficient way to manage and analyze vast amounts of data generated by connected devices with the help of distributed-AI.

Thank you so much for joining us in this interview series! Before we dive in, our readers would love to “get to know you” a bit better. Can you tell us a bit about your ‘backstory’ and how you got started in the AIoT industry?

With over 25 years of experience in the semiconductor industry, I founded and served as the Chairman & CEO of Silicon Image, a leading provider of connectivity solutions that enable HDTVs, set-top boxes, personal computers, game consoles, digital camera, PC and mobile devices to display high-definition content, from 1995 to 2005. As the creator of HDMI and holding more than 50 patents in the field of semiconductor and connectivity technologies, I began to dip my toes into the AIoT industry six years ago, when I saw the need to solve the challenge of barriers. There was so much focus on IoT devices itself, which is now highly powered and capable, but saw an opportunity to build directly into the hardware for optimal results. Enter AI in IoT.

Can you share the most interesting story that happened to you since you began your career?

I’ve had the great privilege to collaborate with some of the most highly skilled teams and prominent companies in the field of tech to establish and develop groundbreaking global standards — DVI for the PC industry and HDMI for the consumer electronics industry.

Ok wonderful. Let’s now shift to the main focus of our interview. Can you tell our readers about the most interesting AIoT projects you are working on now?

Scenera is developing standards and solutions for linking intelligent sensors with AI systems, both in the cloud and in the camera itself, to protect human safety, security, and privacy while optimizing IoT operations for businesses.

Currently, there are too many choices for customers to determine the right AI: IoT Sensors, Edge AI HW, AI Models and Cloud Services. Customers managing facilities will need to pick and choose which AI technology and functions they deploy. But how do you build the right AI Model and where do you run those? Everyone needs a framework to do that. That is what Scenera offers. This is a different business model and there is no competitor.

Scenera provides efficient IoT data management with seamless handling across infrastructure and services. It offers automated custom service creation, predictive modeling, and business data analysis. Additionally, Scenera adopts a customer-centric approach by enabling customers to develop their proprietary IP-based AI models and generative AI Large Language Models (LLM) tailored to their specific requirements.

Listed below are Scenera’s key highlights:

  1. Reduced Labor Costs: AI-powered video analytics can automate tasks that would typically require a large number of human operators. This reduces the need for manual monitoring and analysis, leading to cost savings on labor expenses.
  2. Increased Efficiency: AI algorithms can process and analyze vast amounts of video footage much faster than humans. This increased efficiency means that fewer resources are required to monitor and manage surveillance systems, resulting in cost savings.
  3. Preventing Losses: AI data analytics can quickly detect and respond to security threats, such as unauthorized access or suspicious behavior. By preventing potential losses due to theft, vandalism, or other security breaches, organizations can save money that would have otherwise been spent on repairing damages or replacing stolen items.
  4. Enhanced Maintenance: AI-driven analytics can help predict equipment failures and maintenance needs in surveillance systems. By identifying issues proactively, organizations can conduct timely repairs and replacements, reducing downtime and avoiding costly emergency repairs.
  5. Optimal Resource Allocation: AI data analytics can identify patterns and trends in video data, helping organizations optimize resource allocation. This includes adjusting security personnel deployment, managing surveillance camera placement, and refining security protocols, all of which contribute to cost savings.
  6. Improved Incident Response: AI analytics can prioritize and alert security personnel about critical incidents, allowing them to respond quickly and efficiently. This reduces the risk of damages and losses, ultimately leading to cost savings.

Additionally, Scenera is a founding member of the Network of Intelligent Cameras Ecosystem (NICE Alliance), a global team of industry leaders committed to a unified protocol for computer vision and video analytics. NICE members also include Sony, Nikon, Wistron, Foxconn and others.

Where the introduction of HDMI allowed consumers to enjoy a better experience through wired connections, Scenera and the NICE Alliance are aiming to realize a wireless future enabled through the air with the power of AI, cloud computing and 5G.

What are the 5 things that most excite you about the AIoT industry? Why?

AI-powered video surveillance data analytics brings several exciting aspects that revolutionize security and risk management:

  1. Advanced Threat Detection: AI can identify intricate patterns, behaviors, and anomalies that human operators might miss. This boosts threat detection accuracy, leading to proactive security measures and safeguarding of people and assets.
  2. Real-Time Response: AI analytics process video data instantly, enabling immediate responses to security incidents. This quick reaction time helps prevent crimes, mitigate risks, and enhance overall safety in various environments.
  3. Intelligent Automation: AI automates tedious tasks like monitoring and categorizing video feeds, reducing the workload on human operators. This empowers security personnel to focus on critical tasks, optimizing their efficiency and productivity.
  4. Predictive Insights: AI-driven video analytics extract valuable predictive insights from historical data and patterns. Organizations can anticipate security risks and fine-tune their security strategies, fostering a proactive approach to safety.
  5. Scalability and Cost-Effectiveness: AI data analytics is adaptable to different surveillance setups and scales easily. As technology advances, the implementation cost of AI solutions is likely to decrease, making it accessible to more organizations and industries.

These exciting developments make video surveillance a smarter and more effective tool for safety and security management. The continuous growth of the AI industry in this field promises even more innovative solutions, driving advancements in safety and security worldwide.

What are the 5 things that concern you about the AIoT industry? Can you explain? What can be done to address those concerns?

AI in video surveillance data analytics has various advantages, but concerns still do exist:

  1. Privacy and Data Security: The collection and processing of sensitive data raise worries about privacy and data protection. Mishandling or unauthorized access could lead to breaches and privacy violations.
  2. Bias and Fairness: AI algorithms may inherit biases from training data, leading to discrimination or unfair treatment in threat detection and analysis.
  3. Reliability and Accuracy: AI’s effectiveness depends on data quality. Inaccuracies can result in false positives or negatives, affecting threat detection reliability.
  4. Regulation and Compliance: The growing use of AI in surveillance demands clear regulatory frameworks to balance security needs with individual rights.
  5. Vulnerability to Cyberattacks: Inadequate security measures could expose AI systems to hacking, risking severe consequences in security operations.

Addressing these concerns with ethical guidelines and best practices is vital to gain public trust and ensure responsible AI deployment in video surveillance data analytics.

Can you help articulate to our readers a few of the ways that AIoT can improve our health and improve our lives? What are some real life use cases of Scenera where it’s application will positively impact the world?

Scenera strives to drive innovations that support public health, public safety, and the environment.

As a real-world case, faces of staff and frequent guests in an office can be uploaded while all other images are simultaneously ignored when those particular facial images are present.

Scenera has added an additional category to its objectives aligned with public safety, which is a concern for individuals, communities, and nations worldwide. One example is prevention or mitigation of natural disasters such as wildfires.

In numerous regions in the US, notably California, wildfires have become a significant issue with billions in damages over the years. This is a use case where cameras in public spaces such as mountains, forests, ports, and power stations can be unified with an early-detection system to detect smoke or fires across a large area.

Another emerging category of potential client partners are energy utility companies.

In terms of practical application, you can use video surveillance to look for all anomalies without having to worry about any loss of privacy. Public cameras can for specific faces under court order, but ignore everyone else. The opportunities are endless.

As you know, there are not that many women in your industry. Can you advise what is needed to engage more women into the AI industry?

To encourage more women to enter the AI industry, it may be helpful to introduce AI concepts in early education and career paths, through educational initiatives, workshops, and mentorship programs, fostering interest and confidence in pursuing AI careers.

What is your favorite “Life Lesson Quote”? Can you share a story of how that had relevance to your own life?

“Innovation distinguishes between a leader and a follower.” — Steve Jobs

This has been an inspirational quote for me throughout my career, and words that I have looked back on in every professional chapter of my life. To accomplish something such as creating successful industry standards and patenting HDMI came with a lot of innovative thinking as well as ingenious leaders working together. As a follower in my early days, I attribute my successes to the great leaders I had to look up to.

How have you used your success to bring goodness to the world?

The application of AI to IoT video surveillance data analytics can bring about several positive outcomes that better the world:

  1. Enhanced Security and Crime Prevention: AI-powered surveillance can efficiently detect and respond to security threats, reducing crime rates and enhancing safety for individuals and communities.
  2. Efficient Resource Management: By analyzing patterns of human activity and traffic flow, AI analytics can optimize resource allocation, leading to reduced energy consumption, minimized waste, and improved urban planning.
  3. Quick Emergency Response: Real-time analysis of video data allows for swift emergency response during accidents, disasters, or security incidents, potentially saving lives and minimizing damage.
  4. Environmental Protection: AI video analytics can be applied to monitor and safeguard natural habitats, wildlife, and ecosystems, aiding conservation efforts and promoting sustainability.
  5. Improved Public Services: AI data analytics can optimize public services like transportation, healthcare, and waste management, leading to better service delivery and an overall improved quality of life for citizens.

The positive impacts mentioned highlight how AI video surveillance data analytics can contribute to society and tackle challenges in communities and the environment. Nonetheless, it is vital to carefully balance these advantages with privacy concerns and ethical practices to ensure the responsible and transparent deployment of the technology.

My expertise is in product security, so I’m particularly passionate about this question. In today’s environment, hackers break into the software running IoT devices, for ransomware, to damage brands, or for other malicious purposes. Based on your experience, what should IoT manufacturing companies do to uncover vulnerabilities in the development process to safeguard their IoT products?

The implementation of comprehensive security and privacy measures throughout the entire process is crucial to safeguard IoT products. Manufacturers, developers, and users of devices should have a centralized cloud-based authority to oversee security and privacy in clearly defined protocols to manage security credentials. The authorization of application access to devices should be securely granted by end users, with continuous monitoring by the cloud-based authority to ensure secure data transfer, storage, and subsequent access by authorized applications. The enforcement of consistent and strong rules by the central and cloud-based authority plays a crucial role in addressing this matter.

What are your “5 Things You Need To Create A Highly Successful Career In The AIoT Industry?

  1. Ensuring the utmost priority is given to end users’ privacy is of paramount importance. In the realm of AIoT, particular emphasis must be placed on safeguarding human privacy, particularly in terms of how machines recognize individuals and preventing any potential misuse of personal private information.
  2. AIoTs are designed with the primary objective of prioritizing people’s safety and well-being. To fully harness their potential and enhance the overall quality of life, it is crucial to gain a comprehensive understanding of how to effectively utilize AIoTs.
  3. Gaining a comprehensive understanding of customers’; utilization scenarios for their AIoTs is crucial. Various aspects of facility management, such as janitorial services, equipment maintenance, security and safety, and insurance liability recording, may require AIoT data for distinct business purposes. The process of capturing and analyzing data from AIoTs and subsequently generating valuable business insights plays a pivotal role in enabling customers to enhance operational efficiency and achieve success in their respective industries.
  4. While analytic algorithms are becoming commonplace, the primary concern for end users lies in determining how and where to utilize them cost-effectively. Customers desire the ability to possess customized analytic AI models tailored to their specific environmental setup, and they also seek to optimize these models using their own data. Therefore, what customers require is a framework that empowers them to construct their own analytic service, enabling them to differentiate themselves from their competitors.
  5. Embracing emerging technologies like generative AI or leveraging advanced AI processing capabilities at the edge is instrumental. By integrating and optimizing these new technologies and capabilities, businesses can generate superior business insights. This approach not only helps in winning over customers but also expands market reach.

You are a person of great influence. If you could inspire a movement that would bring the most amount of good to the most amount of people, what would that be? You never know what your idea can trigger. :-)

My dream would be to begin an AI adoption movement in today’s society that shapes and innovates applications across various industries and corporations, ultimately impacting daily lives to be more efficient. This would be made possible by utilizing advancements in AI technology to contextualize and accurately interpret the data generated by ubiquitous AIoTs. This application will greatly contribute to enhancing people’s safety, privacy, and overall convenience in their daily lives.

How can our readers further follow your work online?

You can visit our website at www.scenera.net for the most recent company updates, blog articles, events, and more.

Thank you so much for the time you spent doing this interview. This was very inspirational, and we wish you continued success.