Locus Granted Patent for Machine Learning Models To Accurately Predict Traffic Time for Better Last-mile Deliveries
Predictability of last-mile deliveries is a logistical challenge that continues to affect businesses across various sectors such as e-commerce, 3PLs, etc. Locus’ new patent will enable enterprises to achieve better precision in their last-mile deliveries by factoring in traffic patterns, which have historically been considered too dynamic to map. The patent covers unique technology that analyzes the historical data of traffic and predicts the travel time between origin and destination locations. It also factors in sub-variables such as day of the week and time of day to provide hyper-accurate estimated travel times for logistics providers to get ahead.
“To constantly add value to our growing customer base across 30+ geographies, we at Locus, are pushing our engineering boundaries each day,” said Geet Garg, Founder & CTO, Locus. “The latest patent highlights our relentless effort to bring out new levels of innovation in our product suite, enabling enterprises across industries to drive high-precision logistics operations in any geography, reduce costs and achieve business success.”
To foster a culture rooted in innovation, Locus rolled out a company-wide program in 2018 that empowers all employees to apply for patents and includes regular training sessions, end-to-end support for IPR filings, and much more. Through this initiative, Locus has secured four patents in the last four years, with additional filings already in the pipeline that – collectively – will continue to bring advancements in the company’s unique product suite to serve its customers better.
“Innovation lives within our DNA and we believe that every employee should have an equal opportunity to contribute to the next best idea,” said Nishith Rastogi, Founder & CEO of Locus. “Thus, with the goal to cultivate an environment of entrepreneurship and creativity, we introduced this policy to empower and support our team in their commitment to solving challenges of the last-mile logistics”.
