IQ Crash Course - IoT
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In a brand new series from InterQuest, we're discussing some of the biggest megatrends that are facing the technology industry. Last week we took a look at artificial intelligence - this time it's all about the Internet of Things! Time for a crash course!
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-Scale their workflows for international projects in solar, roads, and pipelines
If you work with complex data, join us to learn how to optimize your own processes and transform your results with FME.MuleSoft for AgentForce : Topic Center and API Catalog
MuleSoft for AgentForce : Topic Center and API Catalogshyamraj55
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This presentation dives into how MuleSoft empowers AgentForce with organized API discovery and streamlined integration using Topic Center and the API Catalog. Learn how these tools help structure APIs around business needs, improve reusability, and simplify collaboration across teams. Ideal for developers, architects, and business stakeholders looking to build a connected and scalable API ecosystem within AgentForce.Addressing Evolving AI Model Challenges Through Memory and Storage, a Prese...
Addressing Evolving AI Model Challenges Through Memory and Storage, a Prese...Edge AI and Vision Alliance
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For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2025/06/addressing-evolving-ai-model-challenges-through-memory-and-storage-a-presentation-from-micron/
Wil Florentino, Senior Segment Marketing Manager at Micron, presents the Addressing Evolving AI Model Challenges Through Memory and Storage tutorial at the May 2025 Embedded Vision Summit.
In the fast-changing world of artificial intelligence, the industry is deploying more AI compute at the edge. But the growing diversity and data footprint of transformers and models such as large language models and large multimodal models puts a spotlight on memory performance and data storage capacity as key bottlenecks. Enabling the full potential of AI in industries such as manufacturing, automotive, robotics and transportation will require us to find efficient ways to deploy this new generation of complex models.
In this presentation, Florentino explores how memory and storage are responding to this need and solving complex issues in the AI market. He examines the storage capacity and memory bandwidth requirements of edge AI use cases ranging from tiny devices with severe cost and power constraints to edge servers, and he explains how new memory technologies such as LPDDR5, LPCAMM2 and multi-port SSDs are helping system developers to meet these challenges.Integration of Utility Data into 3D BIM Models Using a 3D Solids Modeling Wor...
Integration of Utility Data into 3D BIM Models Using a 3D Solids Modeling Wor...Safe Software
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Jacobs has developed a 3D utility solids modelling workflow to improve the integration of utility data into 3D Building Information Modeling (BIM) environments. This workflow, a collaborative effort between the New Zealand Geospatial Team and the Australian Data Capture Team, employs FME to convert 2D utility data into detailed 3D representations, supporting enhanced spatial analysis and clash detection.
To enable the automation of this process, Jacobs has also developed a survey data standard that standardizes the capture of existing utilities. This standard ensures consistency in data collection, forming the foundation for the subsequent automated validation and modelling steps. The workflow begins with the acquisition of utility survey data, including attributes such as location, depth, diameter, and material of utility assets like pipes and manholes. This data is validated through a custom-built tool that ensures completeness and logical consistency, including checks for proper connectivity between network components. Following validation, the data is processed using an automated modelling tool to generate 3D solids from 2D geometric representations. These solids are then integrated into BIM models to facilitate compatibility with 3D workflows and enable detailed spatial analyses.
The workflow contributes to improved spatial understanding by visualizing the relationships between utilities and other infrastructure elements. The automation of validation and modeling processes ensures consistent and accurate outputs, minimizing errors and increasing workflow efficiency.
This methodology highlights the application of FME in addressing challenges associated with geospatial data transformation and demonstrates its utility in enhancing data integration within BIM frameworks. By enabling accurate 3D representation of utility networks, the workflow supports improved design collaboration and decision-making in complex infrastructure projectsENERGY CONSUMPTION CALCULATION IN ENERGY-EFFICIENT AIR CONDITIONER.pdf
ENERGY CONSUMPTION CALCULATION IN ENERGY-EFFICIENT AIR CONDITIONER.pdfMuhammad Rizwan Akram
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DC Inverter Air Conditioners are revolutionizing the cooling industry by delivering affordable,
energy-efficient, and environmentally sustainable climate control solutions. Unlike conventional
fixed-speed air conditioners, DC inverter systems operate with variable-speed compressors that
modulate cooling output based on demand, significantly reducing energy consumption and
extending the lifespan of the appliance.
These systems are critical in reducing electricity usage, lowering greenhouse gas emissions, and
promoting eco-friendly technologies in residential and commercial sectors. With advancements in
compressor control, refrigerant efficiency, and smart energy management, DC inverter air conditioners
have become a benchmark in sustainable climate control solutionsReducing Conflicts and Increasing Safety Along the Cycling Networks of East-F...
Reducing Conflicts and Increasing Safety Along the Cycling Networks of East-F...Safe Software
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In partnership with the Belgian Province of East-Flanders this project aimed to reduce conflicts and increase safety along a cycling route between the cities of Oudenaarde and Ghent. To achieve this goal, the current cycling network data needed some extra key information, including: Speed limits for segments, Access restrictions for different users (pedestrians, cyclists, motor vehicles, etc.), Priority rules at intersections. Using a 360属 camera and GPS mounted on a measuring bicycle, we collected images of traffic signs and ground markings along the cycling lanes building up mobile mapping data. Image recognition technologies identified the road signs, creating a dataset with their locations and codes. The data processing entailed three FME workspaces. These included identifying valid intersections with other networks (e.g., roads, railways), creating a topological network between segments and intersections and linking road signs to segments and intersections based on proximity and orientation. Additional features, such as speed zones, inheritance of speed and access to neighbouring segments were also implemented to further enhance the data. The final results were visualized in ArcGIS, enabling analysis for the end users. The project provided them with key insights, including statistics on accessible road segments, speed limits, and intersection priorities. These will make the cycling paths more safe and uniform, by reducing conflicts between users.Providing an OGC API Processes REST Interface for FME Flow
Providing an OGC API Processes REST Interface for FME FlowSafe Software
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This presentation will showcase an adapter for FME Flow that provides REST endpoints for FME Workspaces following the OGC API Processes specification. The implementation delivers robust, user-friendly API endpoints, including standardized methods for parameter provision. Additionally, it enhances security and user management by supporting OAuth2 authentication. Join us to discover how these advancements can elevate your enterprise integration workflows and ensure seamless, secure interactions with FME Flow.FIDO Seminar: Authentication for a Billion Consumers - Amazon.pptx
FIDO Seminar: Authentication for a Billion Consumers - Amazon.pptxFIDO Alliance
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FIDO Seminar: Authentication for a Billion Consumers - AmazonHigh Availability On-Premises FME Flow.pdf
High Availability On-Premises FME Flow.pdfSafe Software
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FME Flow is a highly robust tool for transforming data both automatically and by user-initiated workflows. At the Finnish telecommunications company Elisa, FME Flow serves processes and internal stakeholders that require 24/7 availability from underlying systems, while imposing limitations on the use of cloud based systems. In response to these business requirements, Elisa has implemented a high-availability on-premises setup of FME Flow, where all components of the system have been duplicated or clustered. The goal of the presentation is to provide insights into the architecture behind the high-availability functionality. The presentation will show in basic technical terms how the different parts of the system work together. Basic level understanding of IT technologies is required to understand the technical portion of the presentation, namely understanding the purpose of the following components: load balancer, FME Flow host nodes, FME Flow worker nodes, network file storage drives, databases, and external authentication services. The presentation will also outline our lessons learned from the high-availability project, both benefits and challenges to consider.Why Its Critical to Have an Integrated Development Methodology for Edge AI,...
Why Its Critical to Have an Integrated Development Methodology for Edge AI,...Edge AI and Vision Alliance
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For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2025/06/why-its-critical-to-have-an-integrated-development-methodology-for-edge-ai-a-presentation-from-lattice-semiconductor/
Sreepada Hegade, Director of ML Systems and Software at Lattice Semiconductor, presents the Why Its Critical to Have an Integrated Development Methodology for Edge AI tutorial at the May 2025 Embedded Vision Summit.
The deployment of neural networks near sensors brings well-known advantages such as lower latency, privacy and reduced overall system costbut also brings significant challenges that complicate development. These challenges can be addressed effectively by choosing the right solution and design methodology. The low-power FPGAs from Lattice are well poised to enable efficient edge implementation of models, while Lattices proven development methodology helps to mitigate the challenges and risks associated with edge model deployment.
In this presentation, Hegade explains the importance of an integrated framework that tightly consolidates different aspects of edge AI development, including training, quantization of networks for edge deployment, integration with sensors and inferencing. He also illustrates how Lattices simplified tool flow helps to achieve the best trade-off between power, performance and efficiency using low-power FPGAs for edge deployment of various AI workloads.Key Requirements to Successfully Implement Generative AI in Edge DevicesOpt...
Key Requirements to Successfully Implement Generative AI in Edge DevicesOpt...Edge AI and Vision Alliance
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Addressing Evolving AI Model Challenges Through Memory and Storage, a Prese...
Addressing Evolving AI Model Challenges Through Memory and Storage, a Prese...Edge AI and Vision Alliance
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Why Its Critical to Have an Integrated Development Methodology for Edge AI,...
Why Its Critical to Have an Integrated Development Methodology for Edge AI,...Edge AI and Vision Alliance
油
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