Matching Sensors Using a Knowledge-Based System

Data integration from multiple sources by the means of sensors requires integrating new data expressed in different forms into historical, temporal and spatial contexts. The technical design of sensors and sensor nodes, and the enhancement of their capabilities are of great interest in terms of specifications for their accuracy and the quality of their metrics.

4.6.2.1. Sensors

Sensors are defined as devices that measure physical (e.g. temperature, force,) or abstract quantities (e.g. the number of people in a room). They measure simple physics and the environment, and can be used for sensing and monitoring various activities, from simple phenomena to complex events and situations. They are integrated and/or connected with a multi-purpose device, depending of their use. When incorporated in smart homogeneous and heterogeneous devices connected to networks, the device is considered as a sensor node using a micro-controller that requires CPU, memory and power.

The modelling and publication of sensor data and their contexts of use consist of using a data representation which is based on the sensor data being annotated with semantic metadata, with the aim of increasing interoperability for sensors and sensing systems, and providing contextual information essential for situational knowledge [203]. This representation is supported by the sensor semantic network ontology (SSN), defining data encodings and web services to store and access sensor-related data [204].

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4.6.2.2. Sensor Semantic Network Ontology

The SSN ontology is a solution elaborated to describe the WSN sensors, their data and their contexts of use. This description allows autonomous or semi-autonomous knowledge agents associated to the deployment of these sensors to assist in deploying, configuring, collecting, processing, reasoning about, and acting on sensors and their observations. It describes sensors in their main characteristics, which include their capabilities, measurement processes, observations and deployments. It provides sensors metadata vocabularies supporting the sensors semantics and the main WSN issues, including the sensor nodes interoperability, data communication policy in terms of sensor nodes parameterisation, use of sensors for their enhanced context adaptation, and data communication limitation for less power consumption [205].

The SSN ontology is of great importance given the wide variety of sensors and sensor nodes, and also the huge volume of sensor real time data requiring its full integration by associating to the data a description of its acquisition and communication policy. It is a support tool for the development of intelligent agents able to modify the sensor nodes’ behaviour to enhance their configuration and optimize their performance in terms of lifetime.

4.6.2.3. The Sensor Mission Matching

The main knowledge domain feature considered in this research to demonstrate the conceptual framework feasibility is the sensor-task matching. This mission assignment consists of allocating a collection of sensors and sensor platforms (sensor node) to one or several monitoring missions with the aim of meeting the missions monitoring requirements.

The monitoring planning process aims at assigning monitoring missions that require sensor mission matching which deals with first identifying potential hazards that might occur in a defined space, and then examine available capabilities that will eliminate these hazards. This can be extended later to include their use for continuous sensing, event detection, pattern identification, location sensing, access control and local control of actuators.

The sensing mission matching is a sensor domain feature which consists of breaking a monitoring mission down into a collection of sensing and monitoring operations, each of which is broken down further into a collection of distinct elementary measurement, control and coordination tasks. Each task has specific capability requirements that enable the accurate measurement of the feature of interest associated to the task.

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On the other hand, the sensor mission matching is a requirement engineering process that supports the measurement requirements and capabilities association, validating in a second step the selection of existing sensor nodes during the individual tasks composition, or suggesting the design of specific sensor nodes. This process is illustrated in Figure 4.8 shown below. The individual tasks composition results in the identification of a group of capabilities already present in existing sensor nodes, or these grouped capabilities are a candidate for the design of new sensor nodes.

Figure 4.8: Sensor capability task matching

4.6.2.4. Sensors Capabilities Grouping

The proposed conceptual framework developed in this research, details the knowledge-based system supported by the sensor knowledge domain shown in Figure 4.9. It provides a structured way to analyse monitoring in terms of individual and group sensing tasks, and assess the effectiveness of various means required for accomplishing those tasks. This analysis is based on matching the knowledge domain requirements to the domain-providing capabilities of available sensors using a requirement engineering process associating capabilities to measurement requirements.

Available sensors data stored in the sensor database [205] can be used to make decisions about which sensors are more or less appropriate for a specific mission requiring the performance of intelligence, surveillance and reconnaissance tasks in a monitoring activity.

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Figure 4.9: Sensor domain model

The selection of the support for the grouping of sensor capabilities depends on the mobility of the domain entities to be sensed and/or monitored. Fixed entities require the use of smart detectors and or monitors whereas the mobile entities can be connected to smart active tags attached to objects or people, using the RFID technology. These tags are sensing and radio-equipped devices and the generic sensor node resulting from the integration of RFID and WSN is a hybrid embedded system wirelessly connected to the WSN.

4.6.2.5. The Sensor nodes Heterogeneity

The sensor nodes heterogeneity is concerned by the presence of heterogeneous nodes that have enhanced capabilities in terms of energy capacity, storage, calculation and communication capability [206], which are both required in a sensor network to increase the network reliability and lifetime. Heterogeneous nodes when adequately defined in the ad hoc WSN can “triple the average delivery rate and provide a 5-fold increase in the lifetime (respectively) of a large battery-powered network of simple sensors” [207].

Heterogeneous nodes are considered in this work to be additional nodes to the existing nodes of the ad hoc WSN. They have homogeneous software architecture, and are different in the sense that they have a different software architecture based on the integration of high-speed microprocessors and high-bandwidth, and long-distance network transceivers. They enable

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the ad hoc WSN to acquire in-network functional and data capabilities, to process and store long term range data, and also exchange data with the main system.