Cucumber AI in Action
06/09/2018
Cucumber's long-term client Independent Stevedoring Ltd (ISL) initially engaged with us in 2016 as they required a new mobile logistics solution to replace their legacy system used to validate, track and load logs onto ships. The new solution had to be intuitive, user-friendly and robust for wharf side use by stevedores. Reliability was a fundamental requirement as shipping delays can be very costly.
Our team developed the new Tracker solution over a short period of time with the ISL product owner involved on a daily basis. The technical solution included a management and customer portal along with a mobile application for wharf side cargo scanning and validation.
Cucumber have since enhanced the solution by implementing an image recognition engine using a computer vision machine learning model. Powered by AI (artificial intelligence), the image recognition engine enables computer assisted identification and counting of logs.
The recent addition of the image recognition engine provides ISL with increased accuracy of log counts while lowering the operational load of the stevedores, allowing them to focus on other tasks. This results in increased throughput and efficiency when loading ships. The images generated by the system are valuable for auditing and traceability purposes as an additional benefit.
The solution has the potential to reduce labour costs and to improve ISL's competitive position in the market, and we're fairly confident ISL are happy they went down this path.
Computer vision is having a positive impact across many industries, from law enforcement to horticulture and health and safety to selling more units of an item of clothing.
In manufacturing, it can check for broken or incomplete products during assembly, or perform automated barcode scanning which may currently be done manually using hand-held scanners. Traditional methods that are still widely used can be time-consuming and open to human error; by implementing an AI Computer Vision based solution, businesses may be able to drive efficiency, improved quality and cost savings.
Understandably, we're excited about our capability in this arena as it marks a milestone in our development as a technology solution provider. The tracking solution our team has developed can be adapted to process a number of other things beyond logs, such as poles, cars, fruit or anything else that humans are currently counting on a regular basis.
Once trained, computer vison will likely be more accurate than its human counterparts. And to demonstrate this, when ISL's Paula came in to see the Cucumber team with her famous cheese rolls, we used the technology to count them for her (which it did accurately!). So whether its fruit, logs or cheese rolls, this solution may be able to help your organisation.
If you'd like to discuss how Cucumber could assist your operation using our image recognition solutions or just want to learn more, please get in touch!
Written by Dean Wood