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Description
The analysis of data from diverse IoT sources, such as sensors and devices, facilitates predictive and prescriptive insights that empower users to address potential anomalies in real time. Concentio® IoT Doctor effectively processes data from various IoT endpoints, notifying users of any faulty incoming data to ensure that issues are resolved before the data is utilized for further analytical purposes. Additionally, the Concentio® Production Line Fault Prediction tool leverages AI to conduct predictive assessments of production line components by analyzing IoT data, videos, and images. Meanwhile, Concentio® Optimal Asset Management scrutinizes incoming information from a network of utility service assets, allowing users to schedule timely maintenance and ultimately reduce capital expenditures by informing strategic asset replacement decisions. This comprehensive approach not only enhances operational efficiency but also significantly contributes to improved asset longevity and performance.
Description
It facilitates device connectivity through widely accepted IoT protocols such as MQTT, CoAP, and HTTP, accommodating both cloud and local installations. ThingsBoard is engineered for scalability, reliability, and high performance, ensuring that your data remains secure and intact. You can provision, monitor, and manage your IoT devices securely by utilizing comprehensive server-side APIs. Establish connections among your devices, assets, customers, or other entities with ease. Efficiently gather and archive telemetry data in a scalable and resilient manner. You can visualize your data using either built-in or personalized widgets and adaptable dashboards, which can also be shared with clients. The platform allows you to create data processing rule chains, enabling you to transform and standardize your device data. It can trigger alerts based on incoming telemetry events, updates to attributes, periods of device inactivity, and user interactions. Build a ThingsBoard cluster to achieve maximum scalability and fault tolerance through a microservices architecture. Furthermore, ThingsBoard accommodates both cloud and on-premises setups, making it a versatile choice for various deployment needs. This flexibility ensures that users can tailor their IoT solutions according to specific requirements and preferences.
API Access
Has API
API Access
Has API
Integrations
Azure Marketplace
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
No price information available.
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Scry AI
Founded
2014
Country
United States
Website
scryai.com
Vendor Details
Company Name
Thingsboard
Country
Ukraine
Website
thingsboard.io
Product Features
IoT Analytics
Activity Dashboard
Activity Tracking
Analytics
Asset Tracking
Data Collection
Data Synchronization
Data Visualization
ETL
Multiple Data Sources
Performance Analysis
Real-Time Analytics
Real-Time Data
Real-Time Monitoring
Status Tracking
Preventive Maintenance
Condition Monitoring
Inspection Management
Maintenance Scheduling
Mobile Access
Predictive Maintenance
Purchasing
Reminders
To-Do List
Vendor Management
Work Order Management
Product Features
IoT
Application Development
Big Data Analytics
Configuration Management
Connectivity Management
Data Collection
Data Management
Device Management
Performance Management
Prototyping
Visualization
IoT Analytics
Activity Dashboard
Activity Tracking
Analytics
Asset Tracking
Data Collection
Data Synchronization
Data Visualization
ETL
Multiple Data Sources
Performance Analysis
Real-Time Analytics
Real-Time Data
Real-Time Monitoring
Status Tracking
