Differences

This shows you the differences between two versions of the page.

--- en:iot-open:data:intro [2019/05/27 09:49] – pczekalski
+++ en:iot-open:data:intro [2020/07/20 09:00] (current) – external edit 127.0.0.1
@@ Line 1: / Line 1: @@
+======  ======
+<box #5374d5></box>
+<box #5374d5></box>
 ====== Data and Information Management in the Internet of Things ======
+<box #5374d5></box>
+<box #5374d5></box>
 At the centre of the IoT ecosystem consisting of billions of connected devices is the wealth of information that can be made available through the fusion of data that is produced in real-time, as well as data stored in permanent repositories.
-This information can make the realisation of innovative and unconventional applications and value-added services possible and will act as an immense source for trend analysis and strategic business opportunities. A comprehensive management framework of data and information that is generated and stored by the objects within the IoT is thus required to achieve this goal((https://www.cbronline.com/internet-of-things/10-of-the-biggest-iot-data-generators-4586937/))
+This information can make the realisation of innovative and unconventional applications and value-added services possible and will act as an immense source for trend analysis and strategic business opportunities. A comprehensive management framework of data and information that is generated and stored by the objects within the IoT is thus required to achieve this goal ((https://www.cbronline.com/internet-of-things/10-of-the-biggest-iot-data-generators-4586937/))
 ((https://www.sam-solutions.com/blog/how-much-data-will-iot-create-2017/))
 ((http://www.enterprisefeatures.com/6-important-stages-in-the-data-processing-cycle/))
@@ Line 17: / Line 22: @@
 Traditional data management systems handle the storage, retrieval, and update of elementary data items, records and files. In the context of the IoT, data management systems must summarise data online while providing storage, logging, and auditing facilities for offline analysis. It expands the concept of data management from offline storage, query processing, and transaction management operations into online-offline communication/storage dual operations. We first define the data lifecycle within the context of the IoT and then discuss some of the phases to have a better understanding of the IoT data management.
+  * "6.1. [[en:iot-open:data:data_lifecycle]]";
+  * "6.2. [[en:iot-open:data:iotdatavsdb]]";
+  * "6.3. [[en:iot-open:data:data_sources]]";
+  * "6.4. [[en:iot-open:data:data_gen_domain]]";
+  * "6.5. [[en:iot-open:data:cfe]]";
+  * "6.6. [[en:iot-open:data:data_storage_models_frameworks]]";
+  * "6.7. [[en:iot-open:data:data_processing_models_frameworks]]";
+  * "6.8. [[en:iot-open:data:data_semantics]]";
+  * "6.9. [[en:iot-open:data:prova]]".

en/iot-open/data/intro.1558950546.txt.gz · Last modified: 2020/07/20 09:00 (external edit)