Semantic Sensor Web Advanced

In this Wiki the following topics are covered:

2.0 Major advancements in Semantic Sensor Web Field

There has been many advancements in Semantic Sensor Web Technologies (SSW) and a result SSW is utilized in various field such as 1) Agriculture 2) Catastrophe Management 3) Building Management 4) Laboratory Management and more. Please note the advancements in SSW is very vast and in this article a few are named.

Agriculture:

Monitoring various environmental attributes are critical to the growth of plants. Environmental attributes that are critical for growers are mainly temperature, moisture, pH, Electric Conductivity (EC) and more. Real-time monitoring in addition to setting alerts for the mentioned sensors were never possible. With creating of SSW growers can now track their plant growing conditions in real-time . A great example of such advancement in agriculture through utilization of SSW is the research conducted in Australian farm where temperature, humidity, pressure, wind speed, and direction of wind in addition to rainfall were monitored using SSW methodology. The architecture of this research project consists of Personal Integration needs, Semantic web, and more in addition to semantic data integration that is where data is centralized to make sensor semantic web technologies meaningful and useful.. The goals of this research is to set threshold to receive alerts in case environmental attributes exceed defined limits.

Catastrophe Management:

Natural catastrophes takes away many people’s lives all around the world every years. Natural catastrophes are such as earthquake, tsunami, heavy rainstorms and more. Fortunately, there has been indicators discovered that if measure accurately at various locations, the occurrence of these kinds of disasters can be predicted by centralizing data.

Building Management (Smart Building):

Managing buildings can be quite sophisticated as the cost of fixing damages is significantly higher than having proper monitoring tools in place to prevent damages from happening. Although the need for such tool was realized a long time ago, only recently through creation of SSW the ability of getting notifications has become possible. There has been many advancements in the SSW field specially in building management industry such as getting notification when water leaks, controlling apartment temperature via smartphone and many more [4]. Below is an example of SSW architecture that could be utilized for managing industrial plants. Laboratory Management: Managing laboratory tests can be quite challenging especially in areas where longevity tests are performed. This sorts of test could be a creep test for a material, reaction test of a certain chemical or wireless transmission test of a circuit. Managing tests can be quite difficult in complex infrastructures where many tests occurs at the same time. Moreover, managing tests across multiple locations can also be quite challenging. The major advancements in SSW allowed for real-time monitoring of laboratory variables via utilization of sensors. The major advancement is this field through introduction of SSW is to have dependable alerts that take more than one factor into consideration before alerting . For example, the alert can go off when pressure and temperature both raises above a certain limit or alert can go off when pressure in one building drops yet pressure in another building remains the same.

3.0 Notable Contributions in Semantic Sensor Web Field

Standardization is a lengthy and difficult process as players in a field that have existing solutions would see any standardization as additional cost to their activities. Open Geospatial Consortium (OGC), an international voluntary consensus standards organization, that has been originated in 1994 is putting efforts to enhance and accelerate the growth of SSW community and standardize sensor information across web. Most of OGC standards has dependency on generalized architecture that are collectively captured in set of documents. The goal of OGC is to provide enhancements in description and meaning of sensor data. In more details, OGC had enabled Sensor Web communication. OGC is in charge of creating open geospatial standards. Moreover, OCG is supported by industry, government, and academic partners to allow for easy creation of geoprocessing technologies known as “plug and play”.

4.0 Current Challenges of Semantic Sensor Web Field

The current challenges in SSW field is lack of standardization which slows down the growth rate of sensor of things. In more details, for semantic sensor web to be meaningful the languages, tags, and labels across various applications, developed by various developers, must be the same. Unfortunately, due to scattered development of various architectures the standardization is not possible, this problem is called vastness. There is also the problem of inconsistency where upon changing the architecture of an existing solution the system logic will no longer holds. In order to resolve this problem there is a need for extensive amount of resources (depends on the size and complexity of system). For example, many existing systems use twelve bits to transfer temperature data to a local computer. However in a SSW, 16 bits of data is acceptable. This inconsistency results in higher data traffic with no additional accuracy improvement. In order for the old system to improve to the new system there is a need of allocating extra bits and changing the buffer requirements which is costly. Assuming the resources required to make the tag requirement is available, there is existence of unnecessary data that requires additional storage space in addition to creating confusion for other SSW members. The only solution remains is changing the hardware requirements which requires a lot of resources. Moreover,

5.0 Future Direction and Vision of Semantic Sensor Web Field

The future direction of Semantic Sensor Web is to have a common and standardized language and tags where information about every sensor can be easily interpreted by various web applications. In more details, the vision of of Semantic Sensor Web is to marry physical sensors and Semantic web technologies and enabling the encoding of sensor description and data with languages standardized by semantic web. Ontologies and other semantic technologies can be potentially the missing bridge between sensor network and web because they can be utilized to improve semantic integration and interoperability. The future Semantic Sensor Web allows the data to be organized, managed, shared, analyzed, and controlled easily. Furthermore, currently real-time extension of the SSW is under development named as sensor wiki. The motivation behind this development is to allow real-time access of the physical world. This would allow for users to be able to surf through their community physical sensors.