The NTT DATA Smart Management Platform for City solution, built on Microsoft Azure, consists of four main components:

Sensors and edge computing: The platform uses a secure end-to-end connection to collect data from various sources, such as IoT devices, sensors, and connected systems. The platform also deploys micro data centers near the sensors, which allow for rapid deployment of resources and faster analysis of sensor inputs. This enables end users to detect incidents and take action quickly.

Predictive and diagnostic analytics: The platform uses advanced analytics to deliver real-time data to locations where data can provide maximum value. The platform also filters the data at the edge, and only sends data that indicates an incident or needs investigation back to the core. This reduces the data transport volumes and response times and lowers the demands on the infrastructure.

Artificial intelligence (AI): The platform uses cognitive analytics to correlate and apply AI and machine learning techniques to the multiple edge data inputs and sources, including historical data, city information, weather data and social media updates. This provides deeper insights to accelerate responses to developing situations and improve planning for future scenarios.

Deep learning: The platform uses the Smart Management Platform to monitor, adjust or move workloads dynamically, based on the specific situation. If additional resources are needed based on an alert, the platform can automatically scale up the network and compute power for the portions of the system that need the additional resources.

The NTT DATA Smart Management Platform for City solution offers a number of key features including:

Centralized data management and analytics engine: The platform can ingest IoT data from virtually any sensor and both structured and unstructured data from non-IoT sources, such as weather, open data portals, social media, mobile GPS, financial and internal agency specific data. The platform also incorporates both real-time alerting and trend analysis over time to predict future events.

Extends and consolidates existing smart technology investment: The platform can integrate with existing smart technology investments, such as IoT devices, sensors, and connected systems, and enhance their capabilities with the platform's features.

Incorporates micro data centers to leave the bulk of the data close to the edge: The platform uses micro data centers to process and analyze the data at the edge, reducing the latency and bandwidth issues. The micro data centers also map disparate data inputs to a common data standard, enabling robust analytics.

Displays all data through a common dashboard for simpler command and control: The platform provides a user-friendly dashboard that displays all the data from the edge and the core, allowing users to monitor and control the system easily.

Security and compliance: The platform incorporates robust security measures to protect edge components and data. Industry-standard encryption protocols, access controls, and threat detection mechanisms are implemented. Compliance with regulatory standards is a fundamental aspect of the platform's design.