# A Survey of Techniques for Discovering, Using, and Paying for Third-Party IoT Sensors
## 4 Gap Analysis and Directions for Novel Research
### Describing of IoT Devices and Their Data  
Existing techniques for describing IoT devices and data require further development to support the global sharing of IoT devices.  
1. Semantic technology is highly relevant to describing IoT devices and their data as it provides the foundations for the development of sharing IoT device solutions. Semantic technology is proposed by the IoT community for providing IoT devices and data descriptions to enable interoperability [63]. The Semantic Sensor Network (SSN) ontology is the leading semantic description of IoT devices and their data and provides the basis of most of the well-known ontologies in this field. However, SSN is not comprehensive as it does not cover the ownership of IoT devices, location, and the measurement format of IoT data. Also, there is other information that is not covered by SSN, and this is required to support the integration and payment of IoT devices (e.g., payment ID for IoT devices, cost of using IoT device, Uniform Resource Identifier (URI), integration protocol, and special token for fetching IoT data from IoT devices). Thus, there is a need for a technique which describes IoT devices and their data and that (1) supports heterogeneous IoT devices and their data as well as heterogeneous IoT applications, and (2) provides a comprehensive description that facilitates all or most of the possible aspects, such as the description of payment and the integration of IoT devices. Early work on this area is published in [64]. The authors have proposed an SSN-based ontology that supports semantic queries, integration, and the payment of IoT devices. However, further development is required to fully support a comprehensive description and heterogeneous IoT application.
2. The problem with semantic description is that it requires both significant effort and considerable expertise in RDF-based ontology definitions and use [65]. We envision a machine learning-based description technique that is able to analyze the data stream of IoT devices to generate automatic semantic descriptions for IoT devices and their data. Early work in this area has been published in [66]. The author has proposed using k-fold cross-validation (CV) to train a novel metadata-assisted cascading ensemble classification framework (MACE) for annotating heterogeneous IoT data autonomously. However, this model does not generate the metadata needed for IoT devices.
3. Storing semantic information in a Blockchain requires a specialized blockchain that has an RDF triple store for the efficient query of IoT devices and data descriptions. Early work in this area is published in [1; 2]. The authors have implemented an RDF triple store inside each of the distributed nodes of the blockchain in order to store semantic descriptions of IoT devices and data as triples. They have called this a  
Figure 3: Our envisioned architecture for sharing IoT devices.  
semantic-based blockchain. However, further development is required to achieve an efficient triple store for a scalable semantic-based blockchain.  
The techniques for describing IoT devices, automatically generating semantic metadata, and storing metadata in a blockchain can be called IoT device registration, as can be seen in Figure 1.