sm-6000ssr/ssp
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ai - powered smart recognition scale
sm-6000 ai infuses enterprise-grade cognitive intelligence into retailers’ operations, delivering high accuracy and recognition speed for rapid product identification. this edge computing technology grants high-speed performance and can be easily deployed in various settings such as fruits and vegetables, dried fruits and nuts to identify loose and bagged produce.
smart recognition
leveraging ai technology, loose and bagged produce can be automatically recognised by the scale's built-in camera. best matched candidates will then be called up on the screen to reduce mis-selection and shrinkage while offering shoppers a fast, one-touch self-serve experience.
fast operation
with the weighing process taking just mere seconds for each item, shoppers' average transaction time is significantly reduced while increasing throughput at the weighing stations. on top of boosting operational efficiency, shrinkage caused by human error and malicious intent can also be mitigated.
wide product compatibility
equipped with intelligence, each item can be accurately recognised by the system even with a different type of eco grocery bag, allowing customers to fully enjoy the benefits of this cutting-edge solution.
infrastructure
ai solutions from digi edge computing are supported by a lean infrastructure that consists of three key elements: scales, ai gateway and ai cloud.
by combining these features, retailers can accelerate learning with a pre-trained library, making deployment easier.
the scales would capture new products and upload them to the ai gateway prior to training and storing them in the cloud. they act as a layer of security between the organization's network and digi ai cloud.
the scale recognition can also be used standalone and does not require a server or cloud connection.
by combining these features, retailers can accelerate learning with a pre-trained library, making deployment easier.
the scales would capture new products and upload them to the ai gateway prior to training and storing them in the cloud. they act as a layer of security between the organization's network and digi ai cloud.
the scale recognition can also be used standalone and does not require a server or cloud connection.
