The NTT Smart Management Platform enables contextual, situational awareness and insights. The complete solution involves many technologies and partners, seamlessly integrated to facilitate your business outcomes. Here’s how:

Sensors and edge computing at work: Using a secure Smart Platform with optional micro data centers located near sensors allows for rapid deployment of ICT resources and faster analysis of sensor inputs to detect incidents and take actions quickly.

Predictive and diagnostic analytics at play: Diagnostic analytics at the edge analyze large volumes of data, but only send data indicating an incident has occurred or needs investigation back to the core. Advanced analytics, running in the platforms core, deliver real-time data to locations where data can provide maximum value. This approach minimizes data transport volumes and response times to reduce the demands on the ICT infrastructure.

Applying artificial intelligence (AI): Cognitive analytics correlate and apply AI and machine learning techniques to the multiple edge data inputs and sources, such as historical data, crime information, weather data or social media updates. This information provides deeper insights for responsive services.

Deep learning at work: The Smart Platform allows the ICT infrastructure to monitor, adjust or move workloads dynamically, based on the specific situation. For example, , if an AMBER alert is issued, the Smart Platform could automatically scale up the network and compute power for the portions of the system that perform enhanced license plate recognition functions or capture higher resolution images than normal.

The platform is built on Azure, leveraging the robust infrastructure and services provided by Microsoft. It seamlessly integrates with Azure products and services, allowing customers to take full advantage of the Azure ecosystem. Additionally, it supports other software and technologies to ensure compatibility with a wide range of systems.

Key Features of NTT’s :

-A centralized data management and analytics engine

-Capable of ingesting IOT data from virtually any sensor and both structured and unstructured data from non-IOT sources such as weather agencies, open data portals, social media, mobile GPS, financial and internal agency-specific data

-Incorporates both real-time alerting and trend analysis over time to predict future events

-Extends and consolidates existing client smart technology investments

-Incorporates micro data centers to leave the bulk of the data close to the edge.

-Maps disparate data inputs to a common data standard, enabling robust analytics

-Displays all data through a single pane of glass for simpler command and control