Co- Founder and CTOof Soracom, Kenta Yasukawa – AITech Interview

Soracom Relay allows customers to use existing RTSP/RTP-compatible cameras for audio and video data transmission. Can you discuss how this feature enhances IoT deployments, especially in terms of computer vision and video analytics?

There are many cameras available today that claim to be “connected to the cloud,” but most of them are tightly integrated into their vendors’ vertical cloud applications and require wholesale replacement of existing hardware to take advantage of these capabilities.

RTSP is a standard protocol already widely used in various IP camera products, making them easy to integrate within a tech stack but typically only in single building on-site CCTV deployments. The ability to securely connect RTSP cameras securely to the cloud opens the door to advanced monitoring and analysis capabilities without needing to change your entire set of cameras to shift to cloud-based video processing.

Soracom Relay enables a complete new set of potential opportunities to create value from existing view/record/replay cameras over to new architectures that connect those same video streams to cloud-based processing. Single-site installations typically use disk-based recorders that implement RTSP/RTP connections so that video streams can be viewed locally, sometimes with additional proprietary cloud features for simple remote-view functionality.

With Relay connecting cameras to Amazon Kinesis Video Streams, we encapsulate the overhead of implementing the RSTP/RTP protocol into the camera’s Soracom connection and let the customer shift to an AWS cloud compute architecture to process and create valuable business-centric insights.

Security is a significant concern when dealing with data transmission, especially in IoT. How does Soracom ensure the security of audio and video data transmitted through Soracom Relay?

The security and privacy of customer data is the highest priority in the Soracom platform. We have multiple layers of security implemented in our platform and also offer services for our customers to build a secure infrastructure that supports the needs of  their particular IoT fleet.

Soracom Relay is an ideal match for the secure architecture at the heart of the Soracom IoT Platform. When we saw this use case we immediately knew that we could mitigate risks and concerns associated with RTSP/RTP connected cameras while opening up new revenue possibilities for customers  by linking cameras that traditionally only have a LAN connection directly to AWS’s video streaming services.

RTP video streams are not encrypted and can be dismissed as a source of IoT data despite the very large numbers of devices deployed in LAN environments. Similarly, the RTSP servers these cameras use have often been implemented with poor administration account credentials.

When IoT devices use Soracom connectivity they benefit from a fully encrypted link for all traffic between the devices and our connectivity platform. In the case of RTSP/RTP cameras, that means that the account login process is completely locked down to the Soracom account and moved out of reach from bad actors. The valuable video streams become tamper free, ensuring both that the stream is trustable and at the same time unavailable for others to access.

To Know More, Read Full Interview @ https://ai-techpark.com/aitech-interview-with-kenta-yasukawa/ 

Diversity and Inclusivity in AI

Safeguarding Business Assets

AITech Interview with Kenta Yasukawa, Co- Founder and Chief Technology Officer at Soracom

Kenta, it would be greatly appreciated if you could provide us with insights into your professional trajectory and background that culminated in your position as the Co-Founder and Chief Technology Officer at Soracom.

In 2010, I was a researcher at Ericsson working on Connected Home, Connected Car and similar early-days IoT projects. I was drawing diagrams with fluffy clouds in the middle saying all the intelligent decisions would be made and things would get smart and collaborate with each other once they are connected to this new cloud. But back then the only available technologies for that purpose were rule-based engines, inference based on ontology, which did not have enough potential to be the intelligence to achieve a true Internet of Things vision.  

I felt there was potential in cloud technologies, but I didn’t fully know yet what the cloud could offer. So, I joined AWS as a solutions architect to find out. I worked with various customers to architect systems in the cloud and apply AWS best practices. That made me think, that by applying cloud technologies and best practices, any system can be made more reliable, scalable and available. It should be possible to build telecom infrastructure on top of cloud and it should enable a highly scalable connectivity platform.

I shared the idea with Ken Tamagawa, my CEO and Cofounder. He believed in the idea and we started to seek a way to execute and along the way met Dan Funato, my COO and Cofounder. We founded Soracom and I led the reinvention of telecom infrastructure on top of AWS cloud.

Leveraging the cloud-native telecom infrastructure, we have started a smart connectivity platform that can offload customers’ undifferentiated common heavy liftings in their IoT journeys and accelerate their time to market so we can achieve a truly connected world together.

The recent announcement  introduces Soracom’s new services that leverage Generative AI (GenAI) for IoT connectivity. Could you explain how Generative AI fits into the IoT ecosystem and what advantages it brings to IoT deployments?

GenAI has tremendous potential in IoT deployments. Besides adding natural language interfaces to IoT applications, GenAI applications using a Large Language Model (LLM) in particular has potential to be used for data analytics and decision making.

For example, we have tested ChatGPT to analyze time series data received from IoT sensors and trackers and confirmed it can provide insight about data as if you have a data scientist dedicated to you. By providing data and asking questions such as “What does this data mean?” and “What trend or outliers do you see in the data?”, an AI can answer in a natural language that you speak. We realized the potential and integrated GenAI to our time series data storage service, Soracom Harvest. The feature is called Soracom Harvest Intelligence and available to anyone as a public beta. An AI based data analytics is just one-click away. As in the example, GenAI can be a glue between people and data, and help them understand data. This can help people look deeper into a particular time period, detect an event and take action. If it has to be done by humans, it’d be cost prohibitive and not be scalable, but with GenAI, things can be automated and scalable.

To Know More, Read Full Interview @ https://ai-techpark.com/aitech-interview-with-kenta-yasukawa/ 

Diversity and Inclusivity in AI

Safeguarding Business Assets

Emerging Data Analytics Trends in 2023: Fostering Diversity and Inclusivity in AI

In the rapidly evolving world of technology, data analytics continues to shape industries and drive innovation. As we delve deeper into 2023, it is crucial to examine the emerging trends that are revolutionizing data analytics and the vital role diversity and inclusivity play in the field of artificial intelligence (AI). This article explores the latest data analytics trends and highlights the importance of fostering diversity and inclusivity to create a more equitable and effective AI landscape.

Data Analytics Trends in 2023:

Augmented Analytics: Augmented analytics leverages machine learning algorithms and AI techniques to automate data preparation, analysis, and visualization, empowering businesses to make data-driven decisions quickly and efficiently. With advanced capabilities, augmented analytics simplifies complex data processes and democratizes access to insights, enabling a wider range of users to harness the power of data.

Natural Language Processing (NLP): NLP techniques enable machines to understand, interpret, and respond to human language in a way that resembles human conversation. In 2023, NLP is predicted to witness significant advancements, making it easier for organizations to extract valuable insights from unstructured data sources like text documents, emails, social media, and customer reviews. NLP-driven sentiment analysis and text mining will become integral parts of data analytics, offering profound insights into customer behavior, market trends, and brand reputation.

Edge Analytics: The proliferation of Internet of Things (IoT) devices has led to an exponential increase in data generated at the edge of networks. Edge analytics allows organizations to analyze data in real-time at the point of collection, reducing latency and enhancing decision-making capabilities. In 2023, edge analytics will play a vital role in enabling data-driven insights in various domains, such as healthcare, manufacturing, transportation, and smart cities.

Diversity and Inclusivity in AI:

While embracing these cutting-edge data analytics trends, it is imperative to foster diversity and inclusivity in the field of AI. Diversity in AI teams, including gender, race, cultural backgrounds, and perspectives, is crucial to building unbiased and ethical AI systems. Here's why:

Avoiding Bias: AI algorithms are only as unbiased as the data they are trained on. Without diverse representation, AI systems can inadvertently perpetuate biases and discrimination, leading to unfair outcomes. A diverse team can identify and mitigate such biases, ensuring that AI systems are developed with fairness and inclusivity in mind.

Addressing Real-World Challenges: AI solutions should address real-world challenges faced by diverse populations. By including individuals from diverse backgrounds in AI development, the specific needs, concerns, and experiences of different communities can be better understood and incorporated into AI models, resulting in solutions that are more responsive and beneficial to all.

Conclusion:

As we navigate the data-driven era of 2023, embracing the emerging data analytics trends while prioritizing diversity and inclusivity in AI is essential. Augmented analytics, NLP, edge analytics, and AutoML are transforming the way organizations harness

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