The new IIoT era brings a new challenge
The scale and coverage of digital intelligence is increasing as enterprises would like to turn their physical assets into intelligent machines. But physical assets are heterogeneous, and it makes building an intelligent machine ecosystem complex. To make Intelligence development more secure and agile, enterprises need to abstracts the complexities of both asset management, networking and hardware dependencies away from the intelligence applications.
Cloud centric is not
Cloud brings lots of improvement for managing datacenter operations, and developing software. However, modern Artificial Intelligence use cases requires sub-millisecond latencies which could not be provided by just-Cloud approach. That is the reason why Edge is the mega trend and building proper Edge infrasture is the first thing inside technology leaders agenda.
Platform of EveryThing
Datasance PoT is the Open Source Distributed Edge Intelligence Platform. PoT brings all the advantages and intelligence functions of Cloud Computing to the locations where data is generated.
By leveraging the potential of Eclipse Foundation Open Source projects, PoT provides true Edge connectivity, and brings Cloud Computing functionalities on to any device with a compute resource. By distributing the intelligence microservices on your Edge devices, PoT enables machine-to-machine autonomous decisions.
Container Management on Edge Devices
PoT is based on Eclipse IoFog. By abstracting the Edge HW resources, and with the zero-trust approach, PoT provides true Edge Native security, and Cloud Native development functionalities for Edge devices. So you can start to manage, build, and run container based intelligence and analytic microservices at the points where data is generated.
Fog Computing Services
Fog Computing is the state-of-the art approach for building true P2P connectivity on Edge Layer. The aim is to extend Cloud Computing capabilities, and bring compute, storage, network, control and decision mechanisms to the Edge Layer for building distributed autonomous Edge-to-Edge decision making.
Uniformly collect data from low power devices near Edge HW
PoT uses the power of Eclipse Hono to enable gateway functions on the Edge devices. You can collect protocol agnostic data from different types of low power sensor devices.
Digital Twins (DT) are the digital representation of physical assets. DTs abstract the complexities of assets management, and help you to build interoperable ecosystem. With PoT, you can build DTs on the Edge.
Don't worry when managing thousands of Edge devices
When it comes to Edge, you need to manage thousands of heterogeneous HW resource. With Pot, you can manage thousands of Edge devices, and microservices from a single management UI
Industrial Use Cases:
Datasance PoT, can be everywhere that data is generated and operational is crucial. Discover some example use cases.
Have to build digital service points where the physical services meet with the shareholders of city.
With Datasance PoT, you can build an infrastructure for real-time autonomous traffic signal management on the intersections, and intelligent public busses and connected public transportation.
5G Base Stations
Top challenges: Implement new 5G radio base stations and turn physical network functions into virtual network functions(VNFs)
With PoT you can deploy VNFs as a container(CNF) on stand alone base stations, also you can deploy predictive maintenance algorithms on base stations to monitor real-time health status of base station, and interfere before break happens.
Take control over your manufacturing shopfloor
The production process mostly includes multiple machines and what happens in particular one machine is result of both what happens inside that machine and what happened form previous machines on the flow. So with Datasance PoT, you can build a distributed machine infrastructure for real-time traceability of process, or implement computer vision and error prevention algorithm or predictive maintenance for each machines.
Picking represent 60% cost of warehouse, you do not have an option for wrong picking
Build a real-time traceability for distribution centers.
Your pickers can decide the most suitable routes for batch picking, and warn operator in the case of wrong picking. Also implement pick2light approach to your picking locations, and create P2P autonomous decisions between picker and locations. Integration with smart gloves to maximize operator efficiency.