Vilicom GIGAWAVE Integrations

AWS IoT Greengrass effectively brings the capabilities of AWS to edge devices, enabling them to locally process the data they create while still leveraging the cloud for management, analysis, and reliable storage solutions. This platform allows connected devices to execute AWS Lambda functions, run Docker containers, or utilize both, enabling real-time predictions based on machine learning models, maintaining data synchronization, and ensuring secure communication among devices—even in the absence of an internet connection. With AWS IoT Greengrass, developers can utilize familiar programming languages and models to design and validate their device applications in the cloud before deploying them to the actual devices. Furthermore, this service can be configured to filter and manage device data, ensuring only essential information is sent back to AWS. Additionally, AWS IoT Greengrass offers seamless integration with third-party applications, local software solutions, and a range of AWS services through its Connectors, enhancing the overall functionality and versatility of edge computing. By incorporating these features, AWS IoT Greengrass empowers businesses to maximize the potential of their connected devices while maintaining operational efficiency.

Develop or implement IoT solutions that integrate both modern and legacy machinery while facilitating connections among suppliers, customers, and a globally distributed workforce. Azure Industrial IoT is founded on the idea that innovative solutions and data should work together seamlessly using industry standards, effectively avoiding vendor lock-in. By enabling rapid asset discovery, providing exceptional global support, and leveraging extensive security knowledge from the chip to the cloud, organizations can achieve scalable outcomes. Maintain control over your IoT solutions while linking existing brownfield equipment and ensuring readiness for new technologies or assets in the future. Create industrial IoT systems that align with industrial devices and frameworks through the use of OPC UA standards. Enhance data interpretation with robust visualizations provided by Azure's managed platform services, open-source tools, and adaptable industrial data models available both on the edge and in the cloud, ultimately driving better decision-making and operational efficiency. This comprehensive approach enables a seamless transition to a more connected industrial environment.

Google Distributed Cloud encompasses a comprehensive suite of managed hardware and software offerings that expand Google Cloud’s capabilities to both edge locations and on-premises data centers. Powered by Anthos, this solution is particularly suited for local data processing, edge computing, and modernization of on-site infrastructure, while also addressing strict requirements for data sovereignty, security, and privacy. With the advantages of Google’s advanced AI, data analytics, and database solutions, users can gain valuable insights and overcome traditional limitations related to scale, performance, and costs when handling data, regardless of its location. You can sustain control and independence over your infrastructure and data, ensuring compliance with stringent regulations, all the while leveraging cloud-native services tailored to your specific environment. This flexibility allows organizations to innovate rapidly while maintaining the highest standards of data management and security.