There are many kinds of big data in peer to peer communication network, traditional big data integration algorithms ignore the classification of big data state. The location correlation between big data cannot be accurately obtained, which leads to the time-consuming process of big data integration and the low acquisition accuracy of big data location correlation. A fuzzy integration algorithm for big data in peer-to-peer communication network based on deep learning is proposed. According to the big data integration conditions of peer-to-peer communication network, the benchmark model of big data integration is constructed by combining semi-supervised deep learning. The marked sample updating model of the prior single classification fuzzy integrated data model is used to process the corresponding sample data. Combining the steady-state and dynamic residuals of the datum model, multiple information grains are obtained. Based on this, kalman filter is adopted to fuzzy fusion of big data to obtain state parameters, and multi-scale analysis is carried out to filter out big data noise. Using the obtained information grains to constrain the characteristic correlation degree of big data, the position correlation of big data is completed. Implement fuzzy integration algorithm design of big data in peer-to-peer communication network based on deep learning. In order to verify the effectiveness of the proposed algorithm, a simulation experiment is designed. Experimental results show that compared with many traditional methods, the proposed algorithm takes less time and the computational complexity of the proposed algorithm is significantly reduced. And the big data integration is more accurate and has better application effect.

Fuzzy Integration Algorithm of Big Data in Peer-to-Peer Communication Network Based on Deep Learning

Unique Carbon monoxide (CO) is a gas made when carbon-based powers and synthetics are scorched deficiently. The slow development of this destructive gas can create cerebral pains, queasiness, heaving, dizziness, and disarray, which are all hazardous to travelers' wellbeing and the climate. The objective of this examination is to make an incorporated framework for a vehicle that can detect and distinguish synthetics like carbon monoxide (CO). Moreover, it persistently takes a look at the degree of gases and shows their focus. It likewise creates a programmed caution when CO levels outperform the ordinary reach, permitting the ventilation framework to be initiated rapidly. An instant message (SMS) is shipped off the approved client through GSM to naturally enact the power windows to dispose of carbon monoxide.

Microcontroller based Ingrained Monitoring of Covellar Carbon Monoxide Identification and Air Revitalizing in Air Skilled Automotives

Facilitating higher photovoltaic penetration in residential distribution networks using demand side management and active voltage control

Electricity is one of the basic needs in humans' daily life. Life cannot be thought without electricity since modernization has made Air Cooler, heating system, and refrigerator, etc as a basic equipment in everyone’s life. Furthermore its widely seen that domestic, agricultural, and industrial settings would not function without electricity so the generation and transmission of the same with less losses is the need of the hour. The biggest problem occurring nowadays is the theft occurring, meters which are used for measuring the consumption of units do not account this power theft and other different tampering occurring in meters. This paper discusses an Internet of Things (IoT)-based smart meter with fault detection and theft detection. Even the present conventional meters can be converted to smart energy meters with a simple change in circuit. It mainly consists of Arduino Uno, ESP8266, AC712 current sensors, etc Where the AC712 senses the current usage and with the help of ESP32 it is sent to the adafruit io IoT platform. From there the utility provider can real-time data like the voltage and current consumption, tariff. The proposed system also detects anomalies and theft occurring in the system with the help of an current sensor by measuring the incoming and outgoing current. The results of every cases has been shown in the adfruit io platform in the real time basis itself. 

Internet of Things based Smart Energy Meter with Fault Detection Feature and Theft Detection

Unique Carbon monoxide (CO) is a gas made when carbon-based powers and synthetics are scorched deficiently. The slow development of this destructive gas can create cerebral pains, queasiness, heaving, dizziness, and disarray, which are all hazardous to travelers' wellbeing and the climate. The objective of this examination is to make an incorporated framework for a vehicle that can detect and distinguish synthetics like carbon monoxide (CO). Moreover, it persistently takes a look at the degree of gases and shows their focus. It likewise creates a programmed caution when CO levels outperform the ordinary reach, permitting the ventilation framework to be initiated rapidly. An instant message (SMS) is shipped off the approved client through GSM to naturally enact the power windows to dispose of carbon monoxide. 

In today’s scenario all the technologies are operated in automatic condition from anywhere around the world. Based on our government system first 100 unit of energy is not calculated by energy meter, which is used to calculate the electricity consumed unit in the consumer node. Generally the IoT’s are used for home automation application such as fan and lamp was controlled by mobile phones based on cloud platform. The existing microcontroller is used to control only one data at a time for cloud based process. However to control the data but cannot provide continues energy to the consumer node. This cloud platform is only stores the dates and control to the controller parts with use of ThinkSpeak website. But in this paper deals with monitoring the energy from the solar and energy meter with help of Arduino controller and home automation is done by IoT with Esp8266 Wifi module. This module is used for control both the data’s and monitoring the energy level of the consumer side. The data from solar and energy meter is sent to the cloud through the Wi-fi module and these data’s are dumped into the arudino controller. The controller controls both the data’s parallely with help of IoT and data’s are displayed in LCD. Thus the results of IoT energy from solar and energy meter are provides continues energy to the consumer for home appliances.

T. Santhoshkumar

Papers

IoT Based Energy Management for Smart Home