Dataset Description

From about 700+ images, 77 classes are identified with at least 1 object from each class. The Dataset is custom built for Construction Foundations Site. The dataset is collected from the year 2000 onwards from Construction Sites using Digital Cameras. The tasks undertaken by the dataset requires us to collect more images related to such Construction Sites using Videos and Internet Images. The Dataset is available at:
KlinterAI Roboflow Universe Dataset

Object Detection Prediction

Computer Vision is found to be useful for producing the Scheduling of tasks from a Construction Site. Using Vision as a sensor from Depth Cameras, the detected objects form an input towards the recognition of activity. The Core application will run an Object Detection Model and an Activity recognition Model. Advanced Computer Vision techniques such as OpenhVINO are used for Performance Improvement.

Activity Recognition

The outcome of a recognized activity is a block of text generated from an image and the objects detected. Such recognized activities compose together to form the BIM (Building Information Modeling) activities in a BIM 4D model. The BIM 4D Model is connected to the BIM 5D Model using the Conceptual Classification Codes presented by Revit which each activity exposes.

Construction Classification Codes

A scrollable list of Activities with Classification Codes, Equipment Name / Number and the Timestamp recorded every 2-5 minutes are presented in the Prototype. An SNMP polling of equipments combined with MQTT polling of Vision Depth Cameras are used to form a standards based Vision Exchange Format Data Model to integrate the Applications in the Foundation Sites.

Sl. No.	NameFromActivity	Object 1	TimeStamp	RandomNumber	SNMP Token	UF Num	Title of Activity	MF Num
1	Earthmoving	Excavator	04/12/2022 12:23	89	bfa14955daca93db2acc6116543d4fa46c7a22b5	G1070	Site Earthwork	31 20 00
2	Earthmoving	Dump Truck	05/12/2022 12:23	81	1c58a446a63e719d7b90156a8998ccc461609ed7	G1070	Site Earthwork	31 20 00
3	Undefined	Person with PPE	06/12/2022 12:23	13	e868a7f71518c30388f725182ee85510c18f306e	G1070	Site Earthwork	31 20 00
4	Earthmoving		07/12/2022 12:23	68	3a02579c191f8558e3fedece867419cb15398b26	G1070	Site Earthwork	31 20 00
5	Earthmoving	Excavator	08/12/2022 12:23	26	5206febf99a349f32b0edf724d9cd1cd9333ebad	G1070	Site Earthwork	31 20 00
6	Earthmoving	Excavator	09/12/2022 12:23	54	a1e4f0b333cb5950624a09c8991401df8c68830e	G1070	Site Earthwork	31 20 00
7		Excavator	10/12/2022 12:23	68	e3579b1e47f273529f0f929453e939a68ede9fd1	G1070	Site Earthwork	31 20 00
8	Earthmoving	Excavator	11/12/2022 12:23	15	da6bfa4b76e2b488e948bab5180520112ebfb18b	G1070	Site Earthwork	31 20 00
9	Earthmoving	Excavator	12/12/2022 12:23	45	e06d6e729196c564869a2c58b1ba7b1454a04b25	G1070	Site Earthwork	31 20 00
10	Earthmoving	Excavator	13/12/2022 12:23	9	8ad73f92d9f9d8ffbb8fcc019cab870008ac555c	G1070	Site Earthwork	31 20 00