IoT-Lite: a lightweight semantic model for the internet of things and its use with dynamic semantics

Abstract

Over the past few years the semantics community has developed several ontologies to describe concepts and relationships for Internet of Things (IoT) applications. A key problem is that most of the IoT related semantic descriptions are not as widely adopted as expected. One of the main concerns of users and developers is that semantic techniques increase the complexity and processing time and therefore they are unsuitable for dynamic and responsive environments such as the IoT. To address this concern, we propose IoT-Lite, an instantiation of the semantic sensor network (SSN) ontology to describe key IoT concepts allowing interoperability and discovery of sensory data in heterogeneous IoT platforms by a lightweight semantics. We propose 10 rules for good and scalable semantic model design and follow them to create IoT-Lite. We also demonstrate the scalability of IoT-Lite by providing some experimental analysis, and assess IoT-Lite against another solution in terms of round trip time (RTT) performance for query-response times. We have linked IoTLite with Stream Annotation Ontology (SAO), to allow queries over stream data annotations and we have also added dynamic semantics in the form of MathML annotations to IoT-Lite. Dynamic semantics allows the annotation of spatio-temporal values, reducing storage requirements and therefore the response time for queries. Dynamic semantics stores mathematical formulas to recover estimated values when actual values are missing.

Healthcare 4.0: A review of frontiers in digital health

“…However, it is also a meta‐ontology that can be extended in order to represent IoT concepts in a more detailed way in different domains. In addition, it is used for knowledge discovery, finding the pattern and unified the information from the heterogeneous IoT platforms (Bermudez‐Edo, Elsaleh, Barnaghi, & Taylor, ).…”

IoT-Stream: A Lightweight Ontology for Internet of Things Data Streams

“…IoT-Lite was inspired by the IoT-A reference model [9] which defined core concepts for the IoT, namely Resources, Entities and Services. It instantiates and extends Device and Sensor concepts from SSN [5]. The focus of IoT-Lite, SOSA and SSN is more on sensing devices and is appropriate for sensor discovery.…”

“…( [1], [2], [3], [4]). Recently some approaches have envisioned the need to provide a lightweight approach to the models, such as IoT-Lite [5], and the standard and popular Semantic Sensor Network model (SSN) [6], which recently has published a lightweight model with its core ontology, SOSA (Sensor, Observation, Sample, and Actuator) [7]. However, these models are centred around devices, but do not pay much attention to the IoT data streams.…”

Analysing real world data streams with spatio-temporal correlations: Entropy vs. Pearson correlation

“…Using spatial-temporal corrections and also considering the background knowledge, historical data and contextual information, we will work to find more enhanced methods 685 and solutions to analyse the correlation versus causation. We also plan to annotate the information in a semantic dynamic model [64] to better interoperate with other data sources.…”