Introduction

For years, safe road construction has been a major challenge for construction managers across the world. This is due to the long-span of construction operation, lack of fixed monitoring cameras, and major impacts on traffic. Construction managers relied on manual inspection and didn't have any image records to assess the situations.
Today, development of Unmanned Aerial Vehicle (UAV) or Drones and Artificial Intelligence (AI), monitoring safety concerns of road construction sites has become easily accessible and very useful. Diatoz Solutions aims to integrate the use of Drones and AI to provide a UAV-based road construction safety monitoring platform. It assesses road construction safety factors such as labourforce on the site, construction vehicles, safety signs that are monitored to make up for the lack of image data at the site.

Assess Road Safety Risks using Drones

Drones or UAVs are the need of the hour. New technologies, such as remote control, autonomous cruise, battery life, and equipped sensors are being developed rapidly and have greatly improved the stability, flexibility, and control of these machines in a number of ways. First, flight and photography schemes are being proposed based on this technology for information collection for any kind of road construction. Second, deep learning algorithms are being utilised to automatically detect and track safety factors. Third, a road construction dataset can be established to help managers with security inspection and to record images. Diatoz aims to get real-time images from the drones that will be input to openCV code. Annotations are used to identify objects.To perform object detection, using models from tensorflow . Also using particle swarm optimizer for motion planning of the drones.

Drones Usage across Industry

UAV technologies are being used in various industries, including construction, agriculture, electricity, transportation etc. The monitoring and identification of safety factors for road construction has improved to a great extent in the recent past. Moreover, AI technology can be applied to realise the automatic monitoring and identification of safety factors. Deep learning algorithms, especially convolutional neural networks, are increasingly popular in this field of computer vision to quickly detect or track targets, like pedestrians and vehicles. Target detection is one of the most basic problems faced by construction managers. Hence, deep learning is used to solve this problem. The monitoring and identification of safety factors based on Drone photography provides an accurate information basis that can be used to make security decisions and supplement the manual safety monitoring steps taken in the road construction field. By utilising autonomous devices like drones on construction sites, construction managers can track and monitor the workflows on the job site in real-time.

Advantages of Using UAVs

There are many advantages of using Drone-based monitoring systems. Firstly, the flexible characteristics of UAVs helps improve the efficiency of safety inspection at the construction site and reduces other risks faced by inspectors. Secondly, it fills the gap in lack of image records on the construction site by providing required photos of the site. The target detection and tracking algorithm improves the efficiency of the site managers in obtaining the on-site target information and helps to reduce manual pressure.

About DIATOZ

Diatoz (Digital A to Z Solutions), is the fastest-growing bootstrapped technology company, providing innovation to the globe catering to multiple domains ranging from venture-backed startups to Fortune 500 companies like Amazon, Tata Communications, L&T, Publicis Sapient, etc. It specialises in Digitally transforming your Innovation, UI/UX Design, and Cloud Infrastructure Services.
Diatoz has worked with key companies in the construction industry Actionable to enable safety rule monitoring, check for any fault in implementation compared to blueprint and detect unwanted objects which could lead to accidents. - Our enterprise solution is driven by scalable microservices that leverage high performance data analytics and search engine capabilities. - We have implemented distributed caching at every layer for performance gains and reduced load on backend systems. - We have used a distributed streaming platform and real time data pipelines for data and content integration. - We made sure we have consistent functionality, single source of truth, and services available for foundational activities. - Through our experienced UI/UX design studio team, we made sure we provide meaningful and relevant experiences to our end users. We do user centric design by understanding the entire journey of a user. - Enable digital teams to roll out applications in an agile way using these services and app container - Have faster and quality release cycles via automated build and deployment and quality check suites.

Conclusion

The accuracy of the object detection algorithm can be improved in future to enhance the uniqueness of UAV shooting and use. This can be done by first working on performance of the UAV itself through improving image transmission. Second, optimising the flight strategy of UAVs on the road construction site, reducing unnecessary flight and saving electricity. Third, optimising the target detection algorithm. In the aspect of algorithm optimization, many articles provide ideas concerning ensuring light weight and speed, further improving the accuracy of detection, and automatically recording and saving the detection results.