The seamless fusion of the virtual world of information with the real physical world of things is consideredthe key for mastering the increasing complexity of production networks in the context of Industry 4.0. Thisfusion, widely referred to as the Internet of Things (IoT), is primarily enabled through the use of automaticidentification (Auto-ID) technologies as an interface between the two worlds. Existing Auto-ID technologiesalmost exclusively rely on artificial features or identifiers that are attached to an object for the sole purposeof identification. In fact, using artificial features for the purpose of identification causes additional effortsand is not even always applicable. This paper, therefore, follows an approach of using multiple natural objectfeatures defined by the technical product information from computer-aided design (CAD) models for directidentification. By extending optical instance-level 3D-Object recognition by means of additional non-opticalsensors, a multi-sensor automatic identification system (AIS) is realised, capable of identifying unpackagedpiece goods without the need for artificial identifiers. While the implementation of a prototype confirms thefeasibility of the approach, first experiments show improved accuracy and distinctiveness in identificationcompared to optical instance-level 3D-Object recognition. This paper aims to introduce the concept of multisensoridentification and to present the prototype multi-sensor AIS.