Industry at the Edge posts

Unlike conventional AI models that rely on cloud computing, Edge AI processes data locally, enabling real-time decision-making, minimizing latency, enhancing security, and reducing operational costs. This technology is already driving greater efficiency and autonomy in industrial settings. In this webinar, we discuss the biggest challenges and solutions to fully harnessing the power of AI at the Edge.

Product servitization has been around for nearly 30 years, but what is different today is the inclusion of emerging and enabling technologies like IoT, Edge Technologies and AI to support the transition from user-owned to provider-owned assets that are wrapped with asset life cycle services.

Computer Vision is experiencing unprecedented growth at the edge, driven by the demand for real-time data processing, enhanced privacy, and operational efficiency. This article delves into deploying a comprehensive Computer Vision solution using Barbara Edge Platform, focusing on the integration of Barbara Video Tools and the cutting-edge Ultralytics YOLOv8 application.

In the highly regulated pharmaceutical industry, GxP compliance is essential for product quality, safety, and efficacy. As regulatory landscapes continue to evolve, pharmaceutical companies must embrace digital transformation to remain compliant and competitive. Barbara’s Edge AI Platform not only help organizations meet GxP compliance but also enhance efficiency, reduce costs, and accelerate innovation.

Developing a data-centric strategy takes companies on a journey from data collection to the creation of advanced AI models. This article explores the stages of an industrial organization's data journey, the challenges they face, and how Barbara’s solutions meet their needs at every step of their digital journey.

In the world of Industry 4.0 and distributed infrastructures, real-time data processing is key to efficient decision-making. Splunk, a leading analytics platform, now integrates with Barbara's edge orchestration platform, enabling deployment on edge nodes and combining its capabilities with artificial intelligence (AI) models to maximize its potential.