Because on our experience on Embedded Systems, we focus on Edge AI which involves deploying AI algorithms and models onto edge devices like sensors and IoT devices, enabling data processing and analysis directly at the source.
This method contrasts with traditional cloud-based AI by offering real-time insights and significantly reduced latency, as it eliminates the need to send data to distant servers. This local processing enhances privacy and security, reduces bandwidth demands, and ensures operational reliability even in limited connectivity environments.
Utilizing machine learning and deep learning, Edge AI equips devices to autonomously analyze and act upon data instantly, which is crucial in applications such as autonomous vehicles for immediate decision-making, smart cities for efficient infrastructure management, and industrial automation for enhanced manufacturing precision. In healthcare, it enables real-time monitoring with wearable devices, and in retail, it provides personalized customer experiences through instant data analysis.
Edge AI marks a significant shift towards more intelligent, efficient, and autonomous systems across various sectors, promising a new wave of technological advancement.
Leveraging AI, we revolutionized a traditional livestock weight data collection system into an intelligent, real-time weight monitoring solution. Integrating an AI model allowed us to automate the analysis of weight data, applying advanced filters and statistical algorithms to identify and average the most frequent weight ranges. This process accurately estimates each animal's weight without the need for manual intervention. Our AI-driven approach streamlines data processing and significantly enhances the accuracy and reliability of livestock weight monitoring, leading to improved farm management and operational efficiency.
Precision seeding electronic system compatible with ISOBUS for Argentine seeders. It consists of head nodes for each row and a central unit, enabling per-row regulation of the application rate based on the established target rate. This is achieved through the control and sensing of the planter's elements, with measurements stored in memory. The system also facilitates report generation and transfer to the cloud via a mobile phone.
Lab equipment automation software with RS232, RS485, OPCUA, and Ethernet connectivity, enabling programming, control, and visualization of flow chemistry processes.
Satellite Communication
Satellite Platform
High Performance Computing
Industrial Instrumentation & Control
Telemetry
Cloud Systems
Video Streaming
Radar
Sensor Adquisition & Procesing
Communications
IOT
Mobile
Test Systems