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MADS Cockpit

MADS Cockpit is the content delivery layer of the MADS IoT Platform by Datakrew, accessible both through the web app and this mobile app

MADS Cockpit is the content delivery layer of the MADS IoT Platform by Datakrew, accessible both through the web app and this mobile app

MADS Cockpit

by Datakrew Pte. Ltd.
MADS Cockpit
MADS Cockpit
MADS Cockpit

What is it about?

MADS Cockpit is the content delivery layer of the MADS IoT Platform by Datakrew, accessible both through the web app and this mobile app.

MADS Cockpit

App Details

Version
1.0.0
Rating
NA
Size
51Mb
Genre
Utilities
Last updated
June 25, 2022
Release date
June 24, 2022
More info

App Screenshots

MADS Cockpit screenshot-0
MADS Cockpit screenshot-1
MADS Cockpit screenshot-2
MADS Cockpit screenshot-3

App Store Description

MADS Cockpit is the content delivery layer of the MADS IoT Platform by Datakrew, accessible both through the web app and this mobile app.

MADS is a distributed IoT Platform for large-scale IoT applications, built for supporting real-time data-intensive intelligent enterprise applications.

MADS removes the complexities of IoT implementation and accelerates the time to value of IoT deployments by providing integrated, secure, tailor-made apps that enable customers and partners to rapidly design & deploy flexible IoT solutions and extract real-time insights to drive competitive advantage.

Using MADS, secure and robust IoT solutions have been deployed in multiple sectors – such as Water, Energy, Manufacturing, Maritime, Buildings, Transportation, etc. The solutions range across asset tracking, condition monitoring, energy management, predictive maintenance, performance warnings, decision insights, etc.

The MADS IoT platform comes with an AppStore, with dedicated apps for different applications. Users can manage IoT assets, build custom dashboards, reports & digital twins, and analyze real-time data while ensuring end-to-end data security.

The main apps in MADS are:

1. Stream Rules: Custom Flow-based Rules Chains

2. IoT Manager: Device Management and OTA Updates

3. Role Manager: Users, Groups, and Access Control

4. Entity Manager: Multi-level Hierarchical Projects

5. Dashboards: No-code Drag-n-Drop Dashboards

6. Data Cruncher: Python IDE for Custom Business Logic

7. Data Insights: Real-time IoT Business Intelligence

8. Digital Twin: Web HMI with Control Interface

9. Alerts: Threshold and Complex Alerts with Grouping

10. Report Wizard: WYSIWYG 16:9 & A4 PDF Reports

11. AI Studio: Auto-ML and No-code ML implementation

12. Tenant Manager: Tenant Resource Management


MADS brings high-performance software engineering to IoT and is built using leading software technologies for next-gen IoT applications, with the following characteristics.

1. Simple: Empower anyone in your team, not just developers, to kickstart IoT use-cases through a powerful yet easy-to-use no-code interface.

2. Swift: Quickly prototype your idea, iterate, and launch use-cases. Full flexibility to customize and deploy for customers in hours instead of months.

3. Agnostic: Operate IoT solutions at scale with dedicated apps to manage devices, projects, and users. Build agnostic dashboards, reports & digital twins.

4. Distributed: Leverage the underlying microservices-based distributed systems architecture, powered by Kubernetes for performance and fault tolerance.

5. Scalable: Ingest millions of data points and create powerful analytics without worrying about scale, baked in horizontal scalability to adjust to load.

6. Available: Meet SLAs with high availability, multi-region replication, failover to redundant systems, built-in logic to detect failed nodes, and auto-heal.

7. Secure: Be assured with data encryption at rest and motion for all data transports with TLS1.2 and hybrid classical & post-quantum encryption.

8. Responsive: Get a fast response time for users with p99 less than 100ms using autoscaling based on advanced algorithms to predict user traffic and self-adjust.

9. Insightful: Build insights and get value from data with a few clicks in a no-code way. Create decision pipelines with stream and batch processing.

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