Designing Smart Control Systems Based on Internet of Things and Big Data Analytics
The Internet of Things (IoT) lay down a platform for global communication among millions of electronic devices connected to the internet. These devices and electronic appliances included both wireless and wired sensors, home appliances such as Television, refrigerator, etc., radio frequency identifications (RFID), and so. Similarly, heterogeneous networks provide a platform for media independent communications. However, there exist several issues in using heterogeneous technologies for IoT communications. These challenges include the co-existence of wireless technologies such as ZigBee, Bluetooth and WIFI, cross-layer communications, high packet loss due to interferences with electronic devices, etc. Similarly, IoT is a new paradigm for interconnecting electronic devices, thus, it needs major refinement for standardising it for various services. In order to address the aforementioned challenges, we proposed a scheme for enabling a generic IoT framework and platform for various IoT embedded devices. The working of the proposed scheme is twofold, (1) discovering and collecting information from IoT enabled devices using sensors and (2) scheduling the working of these appliances based on the data collected using sensors attached to these devices. Further, the data is transferred to Hadoop ecosystem for processing and analyzing to disseminate the relevant information to the citizen. Moreover, the proposed system is tested in a smart home scenario by installing sensors attached to various home appliances. The energy consumption and packet loss occur due to available electronic appliances, and heterogeneous devices are computed and analyzed for planning an optimal scheduling scheme and load balancing. Similarly, data from various authentic sources is analyzed using Hadoop ecosystem and disseminate it to the citizen in real-time.
KeywordsWireless sensor networks Hadoop ecosystem Internet of Things Scheduling Load balancing
This work was supported by Institute for Information and communications Technology Promotion (IITP) grant funded by the Korea government (MSIP) (No. 2017-0-00770). This study was supported by the BK21 Plus project (SW Human Resource Development Program for Supporting Smart Life) funded by the Ministry of Education, School of Computer Science and Engineering, Kyungpook National University, Korea (21A20131600005).
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