Autonomous Context-aware Inventory Management (ACIM)

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Everyday millions of pallets traverse a complex network of producers, transporters, distributors and vendors. At every stage, different rules govern availability, production rates and distribution routes, re-stocking decisions and an avalanche of logistics. There are significant barriers in the largely manual process to tracking and handling pallets at every junction in their trip from producer to destination. In our Autonomous Context-aware Inventory Management (ACIM) project we will devise an autonomous inventory management system that will introduce real-time tracking of pallets as well as accurate localization of entered spaces to dictate handling rules and access rights. ACIM will be autonomous in nature to allow for scalable expansion and expedited handling of large volumes of pallets without human intervention in the decision process. In collaboration with G4 Apps Inc Queens University TRL will work to establish dynamic discovery of handling rules based on the location of each pallet, assigning profiles for locations that dictate pallet-level logistics. We will leverage Queens University's existing Sprouts Sensing platform (http://www.sensornodes.com/) to enable real-time tracking and communication. ACIM, with its racking, localization, communication and interface components, is a multi-faceted solution. We expect significant traction in adoption by merchants and distributors. presenting Ontario as a leaders autonomous Inventory management solutions.