Company
Description
Automation and digitisation are global trends for enterprises to achieve further development. VISUTECH is committed to assisting enterprises in making significant leaps and bounds in their growth. We aim to develop a comprehensive monitoring and controlling system with Artificial Intelligence of Things (AIoT) to improve our clients' businesses by maximising their productivity or enhancing their services/products. The system includes self-developed LoRaWAN sensors for various scenarios, data collection and storage, analysis of data using machine learning algorithms, automated control, and preventive maintenance.
Technology
Our solution is a comprehensive system that includes data collection, cloud storage, analysis, display, and control.
Data Collection:
Data is collected using self-developed wireless sensors that employ various wireless radio frequency technologies (LoRaWAN, NB-IoT, Zigbee, etc.) to support long-range transmission with low power consumption.
Cloud Server & Database:
Collected data is stored in cloud data storage services (AWS, GCP, Azure, etc.) for ease of management and migration. Furthermore, the data is processed with machine learning models (Random Forest, Gradient Boosted Model, etc.) in the cloud server to enable automated control and predictive maintenance.
User Interface:
Data is displayed in various formats according to clients' needs, with the ability to download historical data, generate reports, and set alerts for emergency situations. Additionally, clients can visualise the data through our provided dashboard. The dashboard offers GIS, 3D map, and graphing functions to facilitate clients' usage.
Data Collection:
Data is collected using self-developed wireless sensors that employ various wireless radio frequency technologies (LoRaWAN, NB-IoT, Zigbee, etc.) to support long-range transmission with low power consumption.
Cloud Server & Database:
Collected data is stored in cloud data storage services (AWS, GCP, Azure, etc.) for ease of management and migration. Furthermore, the data is processed with machine learning models (Random Forest, Gradient Boosted Model, etc.) in the cloud server to enable automated control and predictive maintenance.
User Interface:
Data is displayed in various formats according to clients' needs, with the ability to download historical data, generate reports, and set alerts for emergency situations. Additionally, clients can visualise the data through our provided dashboard. The dashboard offers GIS, 3D map, and graphing functions to facilitate clients' usage.
