AI-Powered Construction Progress Monitoring
Budget: ₹37,500 – ₹75,000 INR
PROJECT BRIEF
UTILIZATION OF IMAGES FOR MONITORING PROGRESS IN BUILDING CONSTRUCTION PROJECTS OVERVIEW
SUMMARY
• Monitoring construction progress typically requires technical experts to conduct site visits, which is challenging due to the high volume of projects in Indian cities.
• A machine learning-based solution that assesses construction progress via images can enable agencies (ULBs, state, central) to monitor projects in real-time, minimizing the need for frequent site visits
DESCRIPTION
The solution requires machine learning software with web and mobile (Kotlin) app with interface that processes images from ongoing construction sites to determine the construction stage and assess work completion.
KEY FUNCTIONALITY
• Assess work completion: Analyze images to compare actual progress with blueprints.
• Material tracking: Identify and count materials present onsite.
• User inputs: Allow users to specify details such as the number of buildings in the image and the construction activity (e.g., foundation, superstructure).
• Algorithm selection: Based on the construction activity, the software selects appropriate algorithms for analysis.
• Data input: Develop a custom web and Android (Kotlin) app enabling users to directly input data.
• Different machine learning models will be developed and trained on construction site images for each specific construction stage.
• The software should flag mismatches between selected activity and uploaded images, prompting the user to correct the input.
DELIVERABLES
The software should:
1. Image Analysis: Allow users to upload images, specify construction activities, and assess the construction stage and material count.
2. Progress Comparison: Compare the current construction status with previous images and blueprint benchmarks.
3. Real-Time Insights: Provide real-time data insights to help optimize project management and drive improvements.
4. Customizable Dashboards: Offer dashboards to display live project status, including metrics like labor hours, areas ahead or behind schedule, and completion rates.
5. Data Input: Feature a custom web and Android (Kotlin) app to enable direct data input by users.
6. Error Alerts: Notify users if incorrect images or details are uploaded and prompt for necessary corrections.
Progress reports should be generated every day. Daily progress reports should be provided via Whatsapp.
UTILIZATION OF IMAGES FOR MONITORING PROGRESS IN BUILDING CONSTRUCTION PROJECTS OVERVIEW
SUMMARY
• Monitoring construction progress typically requires technical experts to conduct site visits, which is challenging due to the high volume of projects in Indian cities.
• A machine learning-based solution that assesses construction progress via images can enable agencies (ULBs, state, central) to monitor projects in real-time, minimizing the need for frequent site visits
DESCRIPTION
The solution requires machine learning software with web and mobile (Kotlin) app with interface that processes images from ongoing construction sites to determine the construction stage and assess work completion.
KEY FUNCTIONALITY
• Assess work completion: Analyze images to compare actual progress with blueprints.
• Material tracking: Identify and count materials present onsite.
• User inputs: Allow users to specify details such as the number of buildings in the image and the construction activity (e.g., foundation, superstructure).
• Algorithm selection: Based on the construction activity, the software selects appropriate algorithms for analysis.
• Data input: Develop a custom web and Android (Kotlin) app enabling users to directly input data.
• Different machine learning models will be developed and trained on construction site images for each specific construction stage.
• The software should flag mismatches between selected activity and uploaded images, prompting the user to correct the input.
DELIVERABLES
The software should:
1. Image Analysis: Allow users to upload images, specify construction activities, and assess the construction stage and material count.
2. Progress Comparison: Compare the current construction status with previous images and blueprint benchmarks.
3. Real-Time Insights: Provide real-time data insights to help optimize project management and drive improvements.
4. Customizable Dashboards: Offer dashboards to display live project status, including metrics like labor hours, areas ahead or behind schedule, and completion rates.
5. Data Input: Feature a custom web and Android (Kotlin) app to enable direct data input by users.
6. Error Alerts: Notify users if incorrect images or details are uploaded and prompt for necessary corrections.
Progress reports should be generated every day. Daily progress reports should be provided via Whatsapp.