Smart City — Road & Transport IoT System
Platform of the hardware and software complex for the automation of energy-efficient road transport infrastructure using a wireless network of the LPWAN type, intelligent devices and artificial intelligence technologies (iPavlov Smart City – e-Bus & ITS) A number of technological products for cooperative intelligent transport systems (C-ITS), built on the basis of the technology of integration and subsequent analysis of information flows from heterogeneous sources. The purpose of the complex is to improve traffic safety through the interaction of road infrastructure, cloud information services and driver assistance systems (ADAS).
Technical Architecture
Technology
Tech Platform
Digital Transformation Domain
TR Level
Software Requirements Specifications (SRS) Overview
Project Type
Service Model
Business and Economic Impact
Industry
Project Status
Successfully Deployed in Industry
Unit Cost
$10,000,000
Pricing Model
Social & Environmental Impact
Our AI-powered platform expands the coverage of intelligent transport infrastructure, enabling the deployment of specialized systems in locations lacking traditional electricity supply. This innovative approach uses advanced IoT sensors and energy-efficient technologies to create smart mobility networks anywhere, driving sustainable urban development and accessibility.
By accelerating digital transformation, our project creates new jobs in the digital economy, empowering communities with AI-driven workforce opportunities and fostering talent development in high-tech sectors.
Economic Impact
AI-Powered Economic Impact: Optimizing Smart Transport Infrastructure Costs
Our AI-driven platform delivers up to 90% reduction in electricity costs for smart transport infrastructure (Intelligent Transportation Systems, ITS) by leveraging LPWAN—an energy-efficient data transmission technology. This breakthrough enables infrastructure components to operate on battery power for several years, dramatically decreasing maintenance expenses and maximizing operational efficiency.