Mashups for the Web of Things   Leave a comment

TheWeb of Things (WoT) together with mashup-like applications is gaining popularity with the development of the Internet towards a network of interconnected objects, ranging from cars and transportation cargos to electrical appliances. Here I will provide a brief architectural overview of technologies which can be used in Web of Things mashups with emphasis on artificial intelligence technologies such as conceptualization and stream processing and at data sources and existing Web of Things mashups.

Introduction:

The Web of Things is an emerging concept which extends already existing concepts such as the Sensor Web , where all sensor data and metadata would be published and available to anyone. The things themselves are everyday objects (i.e. coffee mug, chair, truck, robotic arm, etc.) containing a small computing and communicating device. This device is most often a sensor node, however, it can also be an active or passive RFID tag in which case computing is done at the server. The things currently form isolated networks, controlled by different entities, and most often the data remain closed and are rarely used to full potential. Connecting (or federating) the islands of things using web standards is referred to as the Web of Things (WoT).

The mashups for the Web of Things, also referred to as physical mashups, use raw or processed data coming from things, as well as already existing web data and services to build new applications. The development of such technology is expected to have a high impact on humanity, among others on efficiently servicing increasingly urbanized cities with food, transport, electricity and water in an environmentally sustainable way.

One way of looking at the Web of Things—is to see things as organs which detect stimuli. These are then sent via wireless or wired technology, typically on an IP/HTTP network, to processing and storage engines. These engines then crunch the received information and generate knowledge. Sometimes they can also trigger an action, such as sending a tweet. This is somewhat similar to how we, humans, function: we have five senses which are perceived by corresponding organs, then the stimuli are sent to the brain via the nerves, finally the brain processes these stimuli. The result is most often knowledge, and sometimes also actions can be triggered: the brain transmits commands via the nerves to the muscles which then contract and cause moving of hands, legs, talking, etc. One distinction is that while in the case of the humans the sensors and processors are spatially close to each other (e.g. nose and brain or ears and brain), in the case of WoT we may be looking at a global distributed system.

Architectural considerations:

The technological pipeline for the WoT,  The raw data and metadata coming from the network of things can be annotated and enriched—we refer to this as conceptualization—it can be stored using specific approaches for streaming and it can be processed using techniques such as stream mining, event and anomaly detection. WoT mashups can take and use the data at any of these stages.

Network of Things

The things are objects that can be digitally identified by some code such as Electronic Product Code (EPC), Radio Frequency IDentification (RFID), Near Field  Communication (NFC), Internet Protocol (IP) v4 or v6, etc. Using these digital identities, things can then be observed by tracking in production plants, warehouses, etc.; by observing usage patterns, by observing their context, etc.  focus on things that feature sensors and an  embedded device, mostly because the mashup we develop addresses environmental intelligence based on sensor data streams.

The embedded device typically contains four modules: the central processing unit and memory, the communication module, the sensor/actuator and the power source. The CPU controls the embedded device: it tells the sensors to capture data, it sends the data to the storage and/or to the communication module which then transmits them to the destination. A sensor is a device that measures physical phenomena and converts them to a signal that can be read by an observer, or, in our context, by a computer. The communication module typically uses wireless transmission (i.e. IEEE 802.15.4). The operation of the embedded device is constrained by the available power.

Conceptualization of the domain

For small and medium size isolated projects it can be relatively straightforward to know which stream of data measures a given property. Traditional database tables can work well in such situations. However, if we are talking about web scale and are aiming for interoperability, some conceptualization of the WoT domain is needed.

Knowledge about sensors needs to be encoded and structured so that it can be used to its full potential. Additional information such as the phenomena they are measuring, the units of measurement, the location of the sensor node, etc. are needed to accompany the numbers. For instance, if we wanted to know the amount of rain, we should be able to recognize that raindrop, rainfall, and precipitation belong to the same physical phenomena and that all such sensors are a good source for our query. If we were interested in the outside temperatures in the morning, we should be able to infer that a sensor node that is positioned in a stable, is not a good source for us, because it is measuring the temperature inside. If we wanted to find out what is the air pressure in our city, we would need the system to be able to tell which geographical coordinates of a sensor node belong to the area (inverse geocoding). The conceptualization of the domain refers to modeling all this knowledge in a standard way. By using standards also interoperability between different systems can be achieved.

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