An Integral Data Gathering Framework for Supervisory Control and Data Acquisition Systems in Green IoT
ABSTARCT :
In Green Internet of Things, energy consumption research is a hot topic. Our research focuses on Supervisory Control And Data Acquisition (SCADA) system, and it is a system consisting of a plurality of self-organized sensing networks. Live data gathering from numerous Sub-connected SCADA (S-SCADA) networks to make unified decisions based on collected data is one of pivot problem, which has not been well studied. In this article, an integral data-gathering framework is proposed to prolong network lifetime by using sink rotating and Unmanned Aerial Vehicles (UAV) path planning. In the proposed Sink Rotating joint UAV Data Gathering (SR-UAV-DG) framework, the data gathering process is divided into two organic components: (a) S-SCADA in-network data collection. The energy consumption of the network is balanced by selecting the node with the least energy consumption as the sink node. (b) Use UAV for data collection between S-SCADA networks. The theoretical analysis results show that the SR-UAV-DG framework proposed in this article reduces the maximum energy consumption of nodes in the network by 99.21% after 1000 rounds of data. The flight time of UAV is reduced by 16.83%. In the case of unreliable communication links, the data reception rate is guaranteed to reach 91.94%.
EXISTING SYSTEM :
? The existing systems described in this section are not flexible enough to allow users to set the features of a monitored field, such as the type of crop, the type and number of soil sensors, and irrigation system parameters used.
? Therefore, code reuse is impracticable for the irrigation management of agricultural fields which do not fit to the existing system configuration.
? The water balance and matric potential approaches often must take data synchronization into account.
? Therefore, some applications have synchronized the data of previously registered crops, as well as soil and weather data, to precisely determine the irrigation water need for the current developmental stage of the crop.
DISADVANTAGE :
? The best approach to solve this problem using the Internet of Things and it provides a new trend to intelligent traffic management.
? IoT sensor data acquisition and analysis are one of the biggest problems in this present living world.
? So many researchers have dealt and put their effort on this problem, as a result, several types of approaches have developed.
? The framework may issue a few most recent continuous moving data that helps drivers picking ideal paths.
? However, the issue with these systems is that the foundation time, the cost caused for the foundation and support of the system is high.
PROPOSED SYSTEM :
• The proposed system was in correlation with DCS, SCADA, and fully integrated automation, that means manufacture procedures and optimize processes are done at the same time.
• They presented a comprehensive analysis of available IoT middleware systems and proposed a set of functional, non-functional, and architectural requirements for a potential IoT middleware solution.
• The study proposed a middleware for data composition and service discovery by applying a probabilistic approach to meet these challenges.
• The proposed framework enables even in high mobility system and provides novel applications such as safety, emergency traffic plan, and adaptive signal scheduling.
ADVANTAGE :
? To evaluate the performance of the proposed framework, the following metrics are considered for measuring the framework.
? However, in the future, the authors will be considering these issues to evaluate the proposed FSDAA framework's performance.
? The ThingSpeak based domain knowledge systems have used the context - aware data to predict the real-time traffic data for reducing the traffic jams and unforeseen delay.
? In this Simulink model, an external capability of Simulink is used to develop the algorithm.
? We used eastbound traffic and westbound traffic for measuring a number of vehicles are moving on both ends.
|