AI and machine learning are reducing construction site accidents, theft, vandalism and hazardous operating conditions by analyzing 24/7 video feeds in real-time, gaining new predictive insights and contextual intelligence into threats.

According to the National Equipment Register, construction theft losses often exceed $1B a year. The latest model equipment, tools and supplies are the most stolen and the least likely to recover. Only 25% of stolen construction equipment is recovered. Add to that an estimated $13B annually that the cost of accidents and injuries cost the construction industry every year. The urgent need to improve construction site security becomes clear.

Improving Construction Site Security With Machine Learning

Analyzing how the specific conditions, factors, locations and phase a given construction site is operating in contribute to greater site security and safety risks is a perfect application of machine learning. Today and in the future, remote monitoring systems in use to protect construction sites will rely on supervised machine learning algorithms to discover new patterns in historical data. Machine learning-based remote monitoring systems rely on IoT sensors combined with night vision, infrared and thermal sensing cameras to capture real-time data streams.

By combining historical video feeds and images with real-time data feeds, machine learning-based remote monitoring systems provide predictive insights into when potential accidents, thefts, or hazardous operating conditions could occur. AI-based remote monitoring systems providers are setting a fast pace of innovation in this area, which is also reflected in the intuitive design of their dashboards and platform approach to scaling these systems globally. Leaders in this area include Twenty20 Solutions, whose cloud-based platform and approach to usability set the standard in remote construction security. Twenty20 Solutions’ remote monitoring system is entirely browser-based, supports geo-location applications (e.g., RFID, GPS and radar asset tracking) and has a user-customizable dashboard.

10 Ways AI Is Improving Construction Site Security

One of the most valuable takeaways from a recent conference call with construction safety and security leaders who have standardized machine learning-based remote monitoring systems is how much time they save from false alarms. A security director managing construction projects in progress in Miami, Atlanta and Chicago says machine learning has virtually eliminated false alarms at his construction sites. “Our team has fine-tuned machine learning algorithms to the specific patterns of our operations and it’s virtually eliminated false alarms – and focused on predicting theft and break-in attempts much more accurately,” he said.

Based on insights gained from the conference call, here are 10 ways AI is improving construction site security:

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