Infrastructure & Construction

Operations and asset management

Goal: Consolidate your AI strategy by analyzing productivity, building predictive maintenance systems, improving asset revenue and predicting customer demand.

Business model transformation

Goal: integrate services from different suppliers and use their operational data to get insight on how to become more efficient over the board

Procurement and construction

Goal: efficient use of resources, predict risks. Adjust costs with subcontractors and suppliers, with the ultimate goal of minimizing costs. AI provides real-time insights that support negotiating with suppliers

Design, biding and financing

Goal: AI assists in the design review process, bidding process and postmortem analysis by analyzing vast amounts of unstructured data

Smart cities and smart infrastructure initiatives are spreading far and wide across the globe, with many cities reaping the rewards of integrating IOT, digital twins and AI to build systems that can help them plan and stay ahead in terms of future development.

Preventive maintenance using predictive AI enables smart cities to take corrective action and avoid disruptions, collapse, and accidents that can negatively impact residents and overall city functioning.

AI systems require a plethora of data related to assets and asset environments to make intelligent inferences during operations. This data is the key to successful predictive analytics and preventive maintenance through AI.

Infrastructure such as utility pipelines, bridges, dams, roads and buildings require constant inspections to prevent them from failing.

Infrastructure & Construction

Infrastructure such as utility pipelines, bridges, dams, roads and buildings require constant inspections to prevent them from failing.

SMART AI powered Infrascture inspections

Asset monitoring requires smart AI-powered digital inspection platforms (DeepDIVE) to help streamline the inspection data and generate quick reports that enable early decisions related to asset maintenance or management.

DeepDIVE allows for the following:

Streamlining and digitalisation of data gathering and learning processes of NDT in the oil & gas industry
Improvement in the speed and accuracy of NDT inspections (like visual, thermal, UT, wave scan, etc.) using digitisation of data and digitalisation of processes
Build autonomy and AI enablement of the inspection process for assets
Simplification and speeding up of the reporting process, including predictive and preventive detections
Enablement of continuous AI learning to continuously improve inspection accuracy, speed and predictability
Enablement of AI detections of various degradations found in structures; for example, DeepDIVE is built with base-learning models for corrosion, cracks and deformations.
The ability to detect new anomalies and features seamlessly as data is built upon within the platform

With DeepDIVE, the infrastructure inspection workforce is the data scientists (and rightly so) in the AI learning process.

Digital TWINS: INSYD

Along with inspections, infrastructure also uses IIoT to track assets and their integrity. This requires digital twin platforms (INSYD) to provide a live, integrated, real-time view of an asset, enabling smart decisions based on data from different perspectives.

With INSYD, the industry can:

Aggregate information gathering across isolated silos of systems like IoT, control systems, NDT inspections, RBI, robotics, drones and human inputs
Create a unified business-relevant view of the entire asset for easier operational decision-making
Make smarter decisions on shutdowns
Predict failures, perform preventive maintenance, and improve overall regulatory compliance
Achieve business goals and improve worker safety through smarter autonomous industrial solutions
Analyse data across various data streams, corroborate and correlate information, and conduct further investigations where required (the integrated AI engine, namely AI INSYD, enable this.

With INSYD’s real-time view of the asset, infrastructure operations teams can spend less time gathering risk information and more time making relevant business and operational decisions that can improve efficiency, profitability, and regulatory compliance, ultimately reducing business risks and disruptions.

Target Persona

Large-scale land and terrain assessment for the deployment of projects

Surveillance of facilities and monitoring perimeter security

Visual Data

Leverage the ability to process visual data and thermal data of buildings and infrastructure on a single platform; capitalise on tools, like the generation of 3D models, to conduct smart and efficient inspection analysis. The option of digital platform or traditional document reports.

Data Acquisition Tools

Integrate data acquisition tools with the platform and use the platform to automatically and seamlessly link data to asset contexts (labels) to reduce the time and effort spent on data organisation and data referencing.

Continuous AI Learning

Use smart, continuous AI learning and predictive and corroborated analytics (with an expert in control approach) to help build effective and accurate AI pre-processing of buildings’/ assets’ current and progressive condition over time.