Database Report: Sensor Databases and Weather Prediction

This report provides an overview of sensor databases, particularly focusing on their application in weather forecasting. It begins by differentiating sensor databases from traditional databases, highlighting their unique structure and data storage methods. The report then explores various types of sensor database management systems, including relational databases and Oracle Database, along with a discussion of query languages used for data management. It delves into the practical application of sensors in weather forecasting, detailing how weather satellites utilize sensors to collect data on cloud formation, weather events, and global weather systems. The report also examines the types of data collected by these sensors, such as temperature, humidity, and barometric pressure, and mentions public databases like Climate Data Online and the National Digital Forecast Database. Furthermore, it addresses the current limitations of sensor-based weather databases, such as complexity, cost, and database failure, while offering potential solutions to these challenges. The report concludes by emphasizing the importance of sensor databases in obtaining critical weather information for preventing catastrophic events, supported by references to relevant academic literature.

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Introduction
The emergence of the sensor networks has enabled new classes for the application which benefits
a large number of fields. Sensor networks are used for fine grain distributed control, as well as
the environment and the tracking (Elmasri & Navathe, 2015). In this research it will focus on the
sensor databases which are used for tracking of the weather.
Description of the sensor database and how it is different from traditional database
Sensor databases differ from traditional databases in the way they are built, the kind of
information they store and how it is stored (Allen, 2002). Sensor databases are structured such as
a phone book which stores the addresses along with the phone numbers. When it comes to
traditional databases they are document oriented and distributed such as the file folder which
holds everything together (Elmasri & Navathe, 2015). Traditional database are all based on
structured data that in most of the cases are stored in fixed format or as fields in the files.
Types of the sensor database management system currently used
Relational database: This is the most popular data model which is used in the industries. This
is based on the SQL (Elmasri & Navathe, 2015). It is the table oriented that means the data has
been stored in the various access control tables, and each of the key field task would be to
identify each row.

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(Allen, 2002)
Oracle Database: This is an object relational database management which is a collection of the
data which is treated as the unit. this database is designed for the business grid computing, the
most flexible and a cost effective way to manage data and application (Cellary, Morzy &
Gelenbe, 2014).
Describe the query language
This is the programming language which is used for storing as well as managing the data in the
RDBMS. The RDBMS usually use a query language as the standard database language. The
query language thus is computer language that is used in making the queries in the databases as
well as the information systems (Elmasri & Navathe, 2015).
How sensors are used in the weather forecasting.
The meteorologist uses a variety of tools which uses sensors to help them gather the information
in regards to the weather and the climate. One way in which sensors are used in the weather
forecast is through weather satellites (Date, 2006). When it comes to viewing the large weather

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system on the scale of the world, there is use of the weather satellites which highlights cloud
formulation, large weather events such as hurricanes as well as global weather systems. With the
use of the forecaster they are able to see the weather across the whole globe in areas such as the
oceans, poles or perhaps the continents. On every satellite there are two sensors. One is the
visible sensor regarded as the imager that works like a camera in the space and this help in the
gathering of the information on the movement of the clouds and the patterns (Date, 2006). The
sensor is used only during the daylight hours as it captures the reflected light in distinctive ways.
The second is the sounder which is the infrared sensor which reads the temperatures. The higher
the temperature of the object, the more energy it can emit. This enable the satellites to measure
the amount of the energy which is radiated on the surface of the earth.
The type of data collected by the sensors
These sensor-based products are able to track specific sets of the weather related variables such
as the changes in the temperature, the humidity and also the barometric pressure which is used to
generate the forecast with pinpoint accuracy that is personalized to your location (Elmasri &
Navathe, 2015).
Public databases are as follows: one is the climate data online which provides free access to
global historical weather as well as the climate data in additional to station history information.
Another database is the national digital forecast (Coronel & Morris, 2016). This is the suite of
the products which are generated by the national weather services through use of the regional
weather forecast.
Current limitation to sensor-based weather database

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One of the disadvantage of the sensor-databases is that they are complex. A sensor based
database can fulfill many of the requirements as well as solve many problems which are related
to databases (Coronel & Morris, 2016).
Another issue is that of the cost. They require a high initial investment particularly the hardware,
as well as the software. There is a significant investment which is based on the size as well as the
functionality of the needs of the organization (Coronel & Morris, 2016). Another issue is that of
the database failure. In this kind of the database all the files are stored in a single database;
therefore, the chances of the failure of the database can increase.
Solutions to the limitations
When it comes to the issue of complexity, there is a need to train more personnel to be in a
position of understanding the system, and therefore, be able to have a complete set of skills to
enable users to use it properly. When it comes to the costs, there is a need to acquire an
alternative that cost less (Cellary, Morzy & Gelenbe, 2014). On the limitation of the database
failure, there is a need to have a contingency plan or perhaps a backup plan for the data which
has been collected, so that in any case of failure, it is possible to access the same information
again.
Conclusions
This report has examined the different types of databases, particularly the ones used in weather
forecasting. Such equipment is essential to be able to obtain information on the weather
conditions so as to prevent various catastrophic events which occur across the globe.

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References
Abadi, D., Madden, S., & Lindner, W. (2016). Sensor Network Integration with Streaming
Database Systems. In Data Stream Management (pp. 409-428). Springer Berlin
Heidelberg.
Allen, F. H. (2002). The Cambridge Structural Database: a quarter of a million crystal structures
and rising. Acta Crystallographica Section B: Structural Science, 58(3), 380-388.
Cellary, W., Morzy, T., & Gelenbe, E. (2014). Concurrency control in distributed database
systems (Vol. 3). Elsevier.
Coronel, C., & Morris, S. (2016). Database systems: design, implementation, & management.
Cengage Learning.
Date, C. J. (2006). An introduction to database systems. Pearson Education India.
Elmasri, R., & Navathe, S. B. (2015). Fundamentals of database systems. Pearson.