Welcome to the exciting world of deep learning and network awareness!

In today’s rapidly evolving technological landscape, the convergence of artificial intelligence (AI) and network awareness stands out as a pivotal game-changer across diverse industries, particularly in the realm of intelligent vision systems.  This convergence has given rise to powerful platforms and tools, empowering developers to craft applications that seamlessly harness the combined potential of AI and network awareness within an integrated solution.

In this blog, we will explore how the collaboration between Shabodi’s Network-Aware Application Enablement Platform (AEP) and Intel OpenVINO empowers AI with network awareness.

Whether you are a technology enthusiast, an AI/ML developer, a Mobile Network Operator (MNO), or a business leader in the tech industry, this blog will provide valuable insights into the benefits and potential of this powerful combination. Let’s dive in and discover how Shabodi’s AEP and Intel OpenVINO are revolutionizing the world of AI.

Network-Aware Application Enablement Platform (AEP)

Shabodi, a leading company in the North American 5G enterprise application enablement industry, has received the 2023 Enabling Technology Leadership Award for its Network-Aware Application Enablement Platform (AEP).  Shabodi’s AEP propels applications into network awareness by exposing previously inaccessible network functions through monetizable and application-friendly API packages. This empowers application developers in network-intensive environments, enabling rapid development and deployment in a write-once-deploy-everywhere approach. This flexibility fosters the creation of high-quality applications, delivering richer user experiences and enhanced returns-on-investment (ROI). 

Shabodi AEP boasts a versatile range of applications spanning diverse industries.

• Mining: Drones are commonly used on mine sites for surveillance and worker safety. These drones are equipped with optical cameras, LIDAR and infrared cameras, they survey the area and relay results back to remote pilots through video feeds. Fidelity of vision and flight control is provided by continuously and strategically controlling network resources. 
• Ports & Logistics: Smart ports are rapidly evolving with remote-piloted cranes, autonomous vehicles, and sensor-based location tracking of personnel and assets. Remote cranes and logistics management software interact with network-aware applications, providing continuous situational awareness for port administration.
• Public Sector and Government: As public safety is paramount, the use of network-aware video applications enables emergency services and security teams to respond to emergencies swiftly, significantly reducing critical care response times and facilitates efficient handling of potential threats. Network-aware applications enhance overall safety measures for first responders and foster a proactive approach in safeguarding communities.

Unleashing High-Performance AI: Exploring Intel OpenVINO’s Versatile Toolkit

Intel OpenVINO is a robust toolkit specifically crafted for high-performance deep learning applications, addressing a diverse range of tasks such as human vision emulation, automatic speech recognition, natural language processing and recommendation systems. Its primary aim is to extend computer vision and non-vision workloads seamlessly across Intel® hardware, thereby optimizing performance. Through its capabilities, OpenVINO enhances applications by deploying high-performance AI and deep learning inference seamlessly from the edge to the cloud.

OpenVINO toolkit applies to various industries, including industrial applications, retail, safety and security, health and life sciences, gaming, cloud service providers, smart cities, and media and creative services.

Developers using OpenVINO can write an application or algorithm once and deploy it across various Intel architectures, including CPU, integrated GPU (iGPU), Movidius VPU, and GNA.

This flexibility allows for efficient utilization of hardware resources and ensures optimal performance across different devices.

The Open Model Zoo is another important component of OpenVINO, which includes a collection of pre-trained deep-learning models for various vision problems. These models support object recognition, face recognition, pose estimation, text detection, and action recognition.

By leveraging these pre-trained models, developers can save time and resources in building their models from scratch.

Intel OpenVINO and Shabodi, a powerful combination worth looking at!

This integrated solution significantly boosts the precision of video analytics/inference by integrating Quality on Demand (QoD) Network API into the inference process. This enhancement provides three key benefits:

1. Optimized Network Performance: By strategically directing network resources to video feeds with relevant object detections, this approach optimizes network efficiency by prioritizing feeds containing crucial information while deprioritizing less relevant ones. This results in a reduced network infrastructure footprint driving higher sustainability (from reduced power consumption), higher ROI and reduced total cost-of-ownership.
2. Enhanced Object Detection Accuracy: Dynamically adjusting video feeds to have higher bandwidth and lower jitter, upon identifying pertinent objects, achieves unparalleled precision in object recognition. This adaptability optimizes image quality, ensuring crystal-clear identification even in challenging environments or adverse network conditions.
3. Streamlined Business Processes: With a notable reduction in false positives, organizations benefit from streamlined operations and enhanced decision-making. By minimizing unnecessary alerts and erroneous detections, this solution empowers businesses to focus their resources where they matter most, fostering efficiency and productivity.

Together, these transformative enhancements redefine the landscape of video analytics and inference, empowering organizations with unparalleled precision, efficiency, and reliability.

Shabodi has recently developed a Network-Aware Computer Vision using the Intel OpenVINO Toolkit. Read more about this latest innovation and download our brief to learn how to quickly onboard third-party applications by leveraging Shabodi’s Network-Aware AEP and adopting Intel’s OpenVINO Toolkit: https://go.shabodi.com/en/solutions/intel-open-vino-solution-brief