Construction and Architectural Analytics Course

• About 360DigitMG & AiSPRY
• Data Explosion, Digital Transformation & Industrial Revolution 4.0
• Value Stream & Opportunities in Construction
• Raw Data collected in Construction and Architecture
• Basics and cost estimation of Supply Chain
• Standards, Regulations, and Best Practices

AI and Data Science in Building will drive the industry to higher productivity and improved efficiency. Exciting solutions are developed with the adoption of AI in the space of Predictive Maintenance, Production Quality Inspection, Inventory Management, etc. The Data is being churned using AI and Data Science applications to give a competitive edge with available digital Data

• Understand the difference between AI, Data Science, and Machine Learning
• Examples of AI solutions in Construction
• Solutions of Machine Learning in Construction
• Video Analytics in Safety and Risk mitigation
• Text Mining of Customer Reviews
• Cost Reduction through Predictive Maintenance
• AI-driven Automated Quality Assurance
• Supply Chain – Optimized Inventory Management
• Instant Access to Information to Customers via AI-Driven Chatbot

Thanks to Industry 4.0 and the development of the digital world, Modern manufacturing is undergoing huge transformations. The application of Data Science and AI in Manufacturing is high now in all aspects from raw materials procurement to finished product delivery.

The fourth Industrial Revolution deals with the principles of the cyber-physical system (CPS). Machines capable of predicting failures, understanding the maintenance cycle, taking appropriate actions in case of need autonomously are a few examples of smart systems.

• IR 4.0 & its Capability Maturity Roadmap
• IIoT Sensors for Manufacturing
• Wireless Sensor Networks
• IIoT Sensors Data & Cloud Computing
• Smart Manufacturing Setup
• Smart Factories & Role of Pillars of IR 4.0

• Introduction to Big Data in Manufacturing
• Hadoop and its Distributed Framework
• Data Collection - IoT sensors, Inventory, etc.
• Data Storage using Hadoop and its Ecosystems
• Data Processing using Spark on Big Data

Machine Learning in Construction and Building is impacting the bottom-line. Machine Learning applications vary from Machine breakdown predictions, Quality Control, Optimize Supply Chain, etc.

• Confirmatory Analysis using Hypothesis Testing
• Data Mining Supervised Learning
  • Regression for Predicting On-Site Machine Breakdown
  • Classification for Predicting Specific Equipment Breakdown
• Unsupervised Learning
  • Clustering of Building material

The most widely used application of Data Science in manufacturing is performing predictive analytics of machine break down. From the likes of Food and Beverages, Oil and Gases, Tobacco, Automobile, etc all the industries are adopting the machine break down models. Data gathered from SCADA systems and combined with the Data obtained from sensors is used to train the algorithms to predict the incidents up front to manage the production cycle appropriately.

• SCADA Data, Server Data & Cloud Data of Machinery
• Critical Equipment Failures in Machinery
• Wind Turbine Breakdown Models
• Battery Breakdown Prediction Model
• Transformers Trip Breakdown Prediction Model

Raw material requirement is highest in the construction industry. Understanding the various raw material needs upfront will help effectively use the inventory. Also one can place the order for raw materials upfront with the best price if the demand is known upfront.

One major cost in construction is the usage of electricity. Placing IIoT sensors in all required places to get the data for forecasting future usage is pivotal for cost savings. One can also come to know whether any electrical components are being used even when the business is off.

• Supply-Demand Synergies based on Model-Driven Approaches
• Improving the Accuracy of Forecasting Models
• IoT data from Electrical components for Forecasting future consumption

The safety of the workforce is given the highest importance in all industries and the construction industry has even more stringent labor laws. Video analytics helps monitor the workforce during all times and raise proactive alarms if any one of them stands a risk of getting hurt. One can also automatically track attendance.

• Deep Learning and AI techniques to perform Object Recognition
• Neural Network for Automatic Facial Recognition – Resource Tracking