Industry
- Travel and Logistics
Data and AI in Travel Industry for a Memorable Passenger Experience
Highlights
- A key strategy of PostNord, a major communications and logistics player in the Nordics, is ‘win in parcels’. This required optimum utilization of parcel trucks used across mid mile transport.
- They required accurate measurement of fill rate to better plan the utilization of their linehaul trips between terminals and regional hubs and ability to carry more parcels per trip.
- TCS’ touchless, computer vision, and AI-based solution uses security CCTV cameras to measure the fill rate of trucks, helping PostNord improve operations and save on costs
In this article
Overview
PostNord is a major communications and logistics solution provider in the Nordics.
They have ‘win in parcels’ as a key strategy. To achieve more parcels per trip, their linehauls between terminals and regional hubs had to be better utilized. This necessitated accurate measurement of truck fill rate.
The challenge
PostNord wanted touchless, frictionless, real-time measurement of truck fill rate at parcel terminals.
They have depended on production staff to scan the first and last parcels to measure the fill rate of each carrier. Any non-compliance of the scanning process adversely affected the fill rate KPI and impacted operations cost.
They, therefore, needed the fill rate to be measured accurately to create optimum linehaul plans and for real-time optimization of truck departures.
The solution
TCS improved PostNord’s parcel truck fill rate KPI with an artificial intelligence-based, real-time image analytics solution.
TCS developed a touchless, computer vision, and AI-based solution using existing security CCTV cameras to measure the fill rate of transport carriers. The solution uses camera images to measure the fill rate in real time, enabling optimizations based on the process KPIs (line haul planning, people required at gates, loading efficiency) that it calculates using TCS’ proprietary IP.
TCS adopted a research and innovation approach by testing multiple methodologies for best results. A mathematical model uses two-dimensional images, captured by standard CCTV cameras at fixed time intervals, to calculate the total three-dimensional space in a truck. The cameras for this solution were obtained from Axis Communications. Deep-learning models identify the gate status and carrier type. Masking of the individual is also done to comply with GDPR (General Data Protection Regulation) and labor laws.
Terminal managers monitor the fill rate in real time, helping them plan required adjustments and optimizations in operations. TCS’ proprietary computer vision algorithm helps visualize the output within the terminal and remotely in a secure mode.
The solution is hosted in Azure and is deployable in any cloud without any changes. The algorithm can project fill rate at 95% or more in all standard loading scenarios.
The solution has many features:
It is touchless
It is powered by artificial intelligence and computer vision
Ensures real-time data availability and visibility
Improves security at terminals
Reduces ad-hoc trips for carriers
Enables effective decision-making for tactical and operations team
The benefits
PostNord improved parcel truck utilization with efficient linehaul plans, and also saved on cost.
The innovative initiative helped PostNord optimize transport operations at sorting centers. The cost-effective solution uses surveillance camera to improve linehaul planning and operations through optimum capacity utilization of trucks.
State-of-the-art fill rate KPI autonomously generated.
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