Category: Real-time Analytics

Megh VAS performance and validation report on Intel NUC kit

Megh and Intel® performed a performance and validation assessment of Megh Video Analytics Solution (VAS) running on Intel® NUC kits with 11th or 12th generation Intel® Core™ processors. The kits are cost-effective, small-form factor hardware that provide customers with the performance, power, and accuracy they need to run Megh VAS at the edge. Results demonstrate

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Megh’s contextual analytics framework

Contextual analytics refers to the use of data analytics methods that take into account the setting in which data is generated, collected, and analyzed. The goal is to provide a more complete and accurate understanding of the data by considering the context in which it was created. In the field of customer behavior analysis, for

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Megh’s continuous AI model training

Continuous training (CT) of artificial intelligence (AI) models refers to the ongoing process of fine tuning pre-trained AI models with new data, allowing them to continually adapt and improve. This approach is used to keep models up to date with the latest information, trends, and patterns. This results in more accurate predictions and decisions from

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VAS for AI-powered video analytics for buildings and mobile locations

The following piece is from insight.tech, an Intel-sponsored publication leveraging the Intel® Partner Alliance to provide business and technical decision-makers the latest and greatest technology trends and business solutions in the IoT space. Fixed-to-mobile, AI-powered video analytics for buildings By Pedro Pereira. November 16, 2022. Smart buildings deliver continuous streams of data from sensors, cameras,

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Megh VAS Portal: Manage multiple sites through a single pane of glass

Megh’s VAS Portal provides an easy-to-use dashboard that can be accessed via any browser to manage multiple VAS Suite instances. Supported by a powerful microservices cluster on the backend, VAS Suite supports video analytics use cases for public safety, worker safety, and inventory management for deployment in smart buildings, smart warehouses, smart cities, and other

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REST and WebSocket APIs in Nimble

The Nimble application framework Nimble is a fast and lightweight service-based framework for implementing video analytics pipelines targeted for CPU, GPU, FPGA, and SOC platforms. As illustrated below, Nimble sits on top of the Arka Runtime, which manages deep learning inferencing on the targeted platforms and enables seamless integration of The Megh Platform into existing

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Megh VAS SDK

Megh’s fully customizable, cross-platform Video Analytics Solution (VAS) is available as the VAS SDK toolkit and VAS Suite of products. VAS SDK is targeted for enterprises, system integrators (SI), OEMs, and developers, enabling full control to optimize video analytics pipelines and integrate highly customizable AI into applications. VAS SDK is one member of Megh’s family

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Open Analytics: A new approach to intelligent video analytics

The demand for edge analytics is increasing rapidly with the explosion of streaming data from sensors, cameras, and other sources. Of these, video remains the dominant data source with over a billion cameras deployed globally. Enterprises want to extract intelligence from these data streams to create business value. As such, over the past decade, we’ve

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Nimble application framework with cross-platform support

With the release of Megh VAS 100 comes a new addition to the Megh Computing solution stack: the Nimble application framework. Nimble is a fast and lightweight service-based framework for implementing CPU, GPU, and FPGA video analytics pipelines. As illustrated below, Nimble sits on top of Arka, Sira, and Deep Learning Engine (DLE), enabling seamless

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