Survey on automatic control and data acquisition of
electrical appliances
Akanksha Choudhary, Arvind Kumar Pandey
Abstract— IoT is constantly being improved to make it appropriate for cloud-based data monitoring, control, and acquisition via
various electrical appliances. It connects all types of devices to a single platform, allowing them to be monitored and their data
to be arranged to produce meaningful results.. The purpose of this study is to collect data from these devices as well as to
remotely control them. Because power electronics devices operate at high voltage, and the maximum allowed voltage signal in
the case of the ESP32 is 3.3v, the data from the power electronics devices can be fed into an IoT device such as the ESP32
through a potential divider, and the data gathered can be sent to Thing speak, which is an IoT analytics platform service that
provides cloud services for storing, analyzing, and visualizing data. IoT devices can be used to control power electronics
devices, which are used to control electrical appliances. This means that electrical equipment can be controlled remotely via
the cloud. The only criteria will be that the residences be connected to the internet 24 hours a day, seven days a week. When
an IoT device is triggered by the cloud, it sends a signal to the power electronics device to switch at various levels. According to
the command received by the IoT device via cloud, the power electronics device will activate the appliance to work at a
particular level of regulation. This will allow people to operate remotely in hazardous environments with negative health
consequences. Devices close to the location can be managed remotely through IoT in places like mines and chemical
refineries, where health concerns are high. This will significantly improve the lives of those who work there.
Index Terms— Control, Electrical devices, Internet of Things, Monitoring, Power Electronics
1 Introduction
The Internet of Things (IoT) is a global network that connects all
types of devices which can be used in multi ciliary industry
Here they used most of the products which are IOT enabled by
using which we can exchange data. Which gives the better
capability in the field of electrical engineering. Using IOT we can
have different and various substations which can access the
remote devices using the hand held application like. Most of the
power plants across the country they use the IOT devices the
performance monitoring and also for accessing the real time data
which is generated from power plants, IoT is being used to make
circuits more compact and efficient. Power electronics are used to
control items like air conditioners, home appliances, and electric
cars that can communicate with the user via the Internet of Things.
These gadgets send their data to a cloud server, where it is then
received by the user. It allows the user to access info quickly and
effortlessly at any time. This enables for better monitoring and
analysis, as well as a reduction in the time required taking
corrective action if a device does not produce the desired output.
Wireless communication is handled by the ESP32S is the most
reliable WIFI in terms the cost effaced and Bluetooth-ready
module on the market. Unlike its predecessor, the ESP8266, the
ESP32 includes a dual-core processor. A comparison of ESP32,
ESP8266, CC32, and Bee has been conducted. The Wi-Fi and
Bluetooth functions were handled by a single-core ESP8266. The
aforementioned concerns are addressed in the ESP32S, which has
a dual-core Protocol CPU and Application CPU. In addition, the
ESP32S has a number of built-in peripherals that aid in voltage
sensing, as explained in this paper. The device's Wi-Fi/Bluetooth
and internal peripherals use one port, while application code uses
the other. The ESP32S is highly suited for building and
implementing a real-time web server because to its compatibility
and all of these features. Using a smartphone to control a solar
water pumping system, monitoring a photovoltaic system, and
inventing an electronic nose system to detect LPG leaks are just a
few of the projects underway. It may be used to monitor home
temperature, water level, gas leakage, and regulate the fan, motor,
and gas knob, among
other things. It is widely used in agriculture and horticulture
to maintain optima which is used to monitor the health of the crop
and also to calculate the temperate and wind pressure and velocity
which can be assigned them to the ESP32 microcontroller IoT is
already being used in educational settings with power electronic
gadgets to assist bachelor's students. In this article, we'll look at
how power electronics circuits, when paired with Internet of
Things (IoT) devices and software, can help manage street lights
and minimize usage. Following a series of surveys of various IoT
Cloud Platforms. Similarly, a study of IoT middleware platforms
for smart app development has been published. Things Speak is a
cloud-based IoT analytics tool that allows users to store, analyse,
and visualise data. thing Speak can be used to control a variety of
applications, such as a smart irrigation system. DC to DC
converters are widely employed in power systems, electric
vehicles, and small electronic equipment where huge batteries are
not practical. The voltage from the input supply to the load side
output is stepped up using a DC-DC boost converter. For testing,
we can utilise the XL6009 dc-dc boost converter module. It offers
a wide input range of 5–32 V and a large output voltage range of
5–35 V, according to the specifications. MOSFET switches with a
4A current capacity are built-in. passing them to the ESP32
microcontroller IoT is already being used in educational settings
with power electronic gadgets to assist bachelor's students. In this
article, we'll look at how power electronics circuits, when paired
with Internet of Things (IoT) devices and software, can help
manage street lights and minimise usage. Following a series of
surveys of various IoT Cloud Platforms. Similarly, a study of IoT
middleware platforms for smart app development has been
published. Things peak is a cloud-based IoT analytics tool that
allows users to store, analyse, and visualise data.
2 Block diagram and implementation
fig 1:- proposed block diagram
in the proposed system we implement a iot application which can
monitor the voltage using the boost convertor here we can get the
real time data from iot devices and send them to the cloud serve
and monitor the voltage form any where and this is more safe to
any one and this IOT platform imp mentation has been modeled in
the above diagram
3 PROPOSED METHODOLOGY
The above acritude diagram represents the prototype proposed
in this project and which is implemented in two steps in the
first step we use 9v regulated supply which is been connected
to boost convertor and in the second step the output of the
boost converter is send to the circuit which is used for limiting
the current and voltage and current that is obtained from the
variable output boost converter. provided to the input of the
boost converter. And the data is then sent to cloud server
which monitors the complete voltage
4 System Flowchart
The below flowchart give us the complete
implementation steps in the project here a 9v regulated
ds is connected to XL 6009 convertor which is used for
stepping the value and the voltage and the output of this
is send to potential divider circuit and then the output of
the data is send to cloud using Arduino IDE and wich
can be access across the network since it is remote
accessibility using IOT platform and safely any one can
use it
the able and also the fig3 a 9v regulated dc source has
been taken and connected to the booster convert and IC
the
. The potential divider circuit is connected to the ESP32S
IC,
Which is used to generate the 3.3 v of the power and it
changes the boot levels and displays the multiple output
and the voltages and here it contains the different types
of connectivity devices like Bluetooth and Wi-Fi through
which data can be sent to various devices and Things
peak.
Table 1:- list of components
We can access the data from the cloud software like
thingspeak which has been viewed in fig 6 and the table
2 displays the different types of voltages which are used
and here in this prototype we have put the volte to 9 vats
and the output voltage and the boot convertor and
divider circuit has been placed with the different screw
positions as show in the table2 wit xl6009 boost
convertor here the input voltage has been taken was 3.3
volt and this perform and gives a better results with time
tag and it is more cost effective and accurate as shown in
the fig 7 with the different variations of output at the
different time intervals and the throughput results were
calculated
.
Fig 2:- Data flow diagram for proposed system
5. Hardware Implementation and Experiential Results
In this paper we present a prototype to demonstrate the
working condition of the different equipments and the
hardware description has been given here as shown in
Fig 3: XL6009 (boost converter)
Table 2:- variations values between input and output
Fig. 7 Voltage versus time graph indicating the
voltage measured
Fig. 4 ESP32S
6. CONCLUSION AND FUTURE ENHANCEMENT
Iot is used for monitoring the remote server and here we use
the cloud based monitor system which will monitor the voltage
here will use esp325 which is used for checking the voltage
levels which is used in many industries and these can be
accessed remotely and our proposed prototype is more better
in terms for time and cost which can be easily effort able by
any industry
.
Fig. 5 Experimental prototype
6 REFERENCES
[1] J.S. Bridle, “Probabilistic Interpretation of Feedforward
Classification Network Outputs, with Relationships to Statistical
Pattern
Recognition,”
Neurocomputing—Algorithms,
Architectures and Applications, F. Fogelman-Soulie and J.
Herault, eds., NATO ASI Series F68, Berlin: Springer-Verlag, pp.
227-236, 1989. (Book style with paper title and editor)
Fig. 6 ThingSpeak channel
[2] W.-K. Chen, Linear Networks and Systems. Belmont, Calif.:
Wadsworth, pp. 123-135, 1993. (Book style)
[3] H. Poor, “A Hypertext History of Multiuser Dimensions,”
MUD History, http://www.ccs.neu.edu/home/pb/mud-history.html.
1986. (URL link *include year)
[4] K. Elissa, “An Overview of Decision Theory," unpublished.
(Unplu- blished manuscript)
[5] R. Nicole, "The Last Word on Decision Theory," J.
Computer Vision,
submitted for publication. (Pending publication)
[6] C. J. Kaufman, Rocky Mountain Research Laboratories,
Boulder, Colo., personal communication, 1992. (Personal
communication)
[7] D.S. Coming and O.G. Staadt, "Velocity-Aligned Discrete
Oriented Polytopes for Dynamic Collision Detection," IEEE Trans.
Visualization and Computer Graphics, vol. 14, no. 1, pp. 1-12,
Jan/Feb 2008, doi:10.1109/TVCG.2007.70405. (IEEE Transactions
)
[8] S.P. Bingulac, “On the Compatibility of Adaptive
Controllers,” Proc. Fourth Ann. Allerton Conf. Circuits and
Systems Theory, pp. 8-16, 1994. (Conference proceedings)
[9] H. Goto, Y. Hasegawa, and M. Tanaka, “Efficient
Scheduling Focus- ing on the Duality of MPL Representation,”
Proc. IEEE Symp. Compu- tational Intelligence in Scheduling
(SCIS ’07), pp. 57-64, Apr. 2007,
doi:10.1109/SCIS.2007.367670. (Conference proceedings)
[10] J. Williams, “Narrow-Band Analyzer,” PhD dissertation,
Dept. of Elec- trical Eng., Harvard Univ., Cambridge, Mass., 1993.
(Thesis or disserta- tion)
[11] E.E. Reber, R.L. Michell, and C.J. Carter, “Oxygen
Absorption in the Earth’s Atmosphere,” Technical Report TR-0200
(420-46)-3, Aero- space Corp., Los Angeles, Calif., Nov. 1988.
(Technical report with report number)
[12] L. Hubert and P. Arabie, “Comparing Partitions,” J.
Classification, vol.
2, no. 4, pp. 193-218, Apr. 1985. (Journal or magazine citation)
[13] R.J. Vidmar, “On the Use of Atmospheric Plasmas as
Electromagnetic Re- flectors,” IEEE Trans. Plasma Science, vol.
21,
no.
3,
pp.
876-880,
available
at
http://www.halcyon.com/pub/journals/21ps03-vidmar, Aug. 1992.
(URL for Transaction, journal, or magazine)
[14] J.M.P. Martinez, R.B. Llavori, M.J.A. Cabo, and T.B.
Pedersen, "Inte- grating Data Warehouses with Web Data: A
Survey," IEEE
Trans. Knowledge and Data Eng., preprint, 21 Dec. 2007,
doi:10.1109/TKDE.2007.190746.(PrePrint)