IOT based fuel monitoring for future vehicles.
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This document proposes an IoT-based fuel monitoring system for vehicles to avoid financial losses from inaccurate fuel filling records. The system uses a flow sensor activated by fuel flow to calculate the amount filled and notify the owner. It sends the fuel data to the cloud and tracks the filling location via GPS on the user's phone. The system architecture involves a flow sensor, microcontroller, and cloud server for data storage. It aims to allow users to check accurate fuel amounts filled and locations to prevent losses from incorrect records.
![International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395 -0056
Volume: 04 Issue: 02 | Feb -2017 www.irjet.net p-ISSN: 2395-0072
© 2017, IRJET | Impact Factor value: 5.181 | ISO 9001:2008 Certified Journal | Page 1361
IOT BASED FUEL MONITORING FOR FUTURE VEHICLES.
Prof.J.N.Nandimath,Varsha Alekar, Sayali Joshi, Sonal Bhite, Pradnya Chaudhari.
Department Of Computer Engineering STES, Smt Kashibai Navale College Of Engineering, Pune
Savitribai Phule Pune University
-----------------------------------------------------------------------***--------------------------------------------------------------------------------------
Abstract—In today's world, actual record of fuel filled and
fuel consumption in vehicles is not maintained. It results in
a financial loss. To avoid this we are implementing an IOT
fuel monitoring and tracking system. We can use the reed
switch which works according to the principle of Hall Effect
for sensing the amount of fuel filled in the vehicle. So as
soon as agent starts filling petrol in your bike/car, the flow
sensor is activated. This flow sensor will be active till flow
ends. Once flow ends it will calculate the amount of fuel
filled and directly notify on your mobile phone. If the phone
is not available then it will store this data on cloud.
Keywords: Reed Switch, Flow Sensor ,IoT ,Flow
rate, Tail pipe emission.
I. INTRODUCTION
Flow sensor is typically output of pulses proportional
to the instantaneous flow rate which means that to
interpret them it is necessary to implement simple
frequency counter. Since this project uses a fuel flow
sensor containing a Hall Effect sensor that output a
pulse rate proportional to flow rate, so not only it is a
useful project in its own right but it also
demonstrates a very useful technique that you can
use in a wide range of projects that need to measure
the rate at which something happens (an electronic
wind instrument, for example). Flow rate can
be determined by different techniques like change in
velocity or kinetic energy. Here we have determined
flow rate by change in velocity of fuel. Velocity
depends on the pressure that forces the through
pipelines. As the pipes cross-sectional area is known
and remains constant, the average velocity is an
indication of the flow rate. The basis relationship for
determining the liquid flow rate in such cases is Q=V x
A, where Q is flow rate/total flow of fuel through the
pipe, V is average velocity of the flow and A is the
cross-sectional area of the pipe (viscosity, density and
the friction of the liquid in contact with the pipe also
influence the flow rate of fuel).
• Pulse frequency (Hz) = 7.5Q, Q is flow rate in
Litres/minute
• Flow Rate (Litres/hour) = (Pulse frequency x 60
min) / 7.5Q
In other words:
• Sensor Frequency (Hz) = 7.5 * Q (Litres/min)
• litres = Q * time elapsed (seconds) / 60
(seconds/minute)
• litres = (Frequency (Pulses/second) / 7.5) * time
elapsed(seconds)/60
• litres = Pulses / (7.5 * 60) Once the flow started,
application will start
reading pulses and convert it into litres and then send to
cloud server. Mobile application will also track location
where fuel has been deposited.
Fig 1. Flow Sensor
II. RELATED WORK
[1] Optimal Energy and Catalyst Temperature
Management of Plug-in Hybrid Electric
Vehicles for Minimum Fuel Consumption and
Tail-Pipe Emissions. In this paper, they
develop a method to synthesize a supervisory
power-train controller (SPC) that achieves
near-optimal fuel economy and tail pipe
emissions under known travel distances. We
first find the globally optimal solution using
the dynamic programming (DP) technique,
which provides an optimal control policy and
state trajectories. Based on the analysis of the](https://image.slidesharecdn.com/irjet-v4i2266-171120064613/85/IOT-based-fuel-monitoring-for-future-vehicles-1-320.jpg)
![International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395 -0056
Volume: 04 Issue: 02 | Feb -2017 www.irjet.net p-ISSN: 2395-0072
© 2017, IRJET | Impact Factor value: 5.181 | ISO 9001:2008 Certified Journal | Page 1362
optimal state trajectories, a new variable
energy-to-distance ratio (EDR), is introduced
to quantify the level of battery, state-of
charge (SOC) relative to the remaining
distance. This variable plays an important
role in adjusting both energy and catalyst
thermal management strategies for PHEVs. A
novel extraction method is developed to
extract adjustable engine on/off ,gear-shift,
and power-split strategies from the DP
control policy over the entire state space.
Based on the extracted results, an adaptive
SPC that optimally adjusts the engine on/off ,
gear-shift, and power-split strategies under
various EDR and catalyst temperature
conditions was developed to achieve near-
optimal fuel economy and emission
performance.
[2] Wireless sensor network based smart home:
Sensor selection, deployment and
monitoring. This paper details the
installation and configuration of sensors in
an elderly person's house a smart home in
the making in a small city in New Zealand.
The overall system is envisaged to use
machine learning to analyze the data
generated by the sensor nodes. The novelty
of this project is that instead of setting up an
artificial test bed of sensors within the
University premises, the sensors have been
installed in a subject's home so that data can
be collected in a real not artificial
environment.
III. PROPOSED SYSYTEM
The location history of individual fleet vehicles allows
precisely time managed, current and forward journey
planning, responsive to changing travelling
conditions. To avoid this we are implementing an IOT
fuel monitoring and tracking system. So as soon as
some agent starts filling petrol in your bike/car the
flow sensor activated. This flow sensor will be active
till flow ends. Once flow ends it will calculate the
amount of fuel filled and directly notify on yours
mobile phone.
IV.SYSTEM ARCHITECTURE:
. The following figure gives a brief idea about the
system architecture
Fig 2. System architecture
The location history of individual fleet vehicles allows
precisely time managed current and forword journey
planning ,responsive to changing travelling conditions. To
avoid this we are implementing an IOT based fuel
monitoring for future vehicles. When agent start filling
petrol in your vehicle flow sensor will get activated. This
sensor will active till the flow ends. Once the flow ends it
will calculate how much amount of fuel is inserted and
this information will directly notify on your mobile. Also
location can track via GPS so we know from where we
have deposited the fuel.
V.PERFORMANCE REQUIREMENT
[1] JVM should be tuned on mobile to provide extra
address space to application.
[2] Raspberry-pi 3 will be used.
[3] Hardware should have 1 GB RAM and good
processor.
VI. FLOW SEQUENCE
[1] Initially power get on and flow sensor get started.
[2] Flow sensor will wait till flow of fuel get started.
[3] Flow sensor will calculate how much amount of
fuel is filled.
[4] Then this calculated information of fuel is send to
the cloud.
[5] At the same time location is fetch by the users
mobile.](https://image.slidesharecdn.com/irjet-v4i2266-171120064613/85/IOT-based-fuel-monitoring-for-future-vehicles-2-320.jpg)
![International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395 -0056
Volume: 04 Issue: 02 | Feb -2017 www.irjet.net p-ISSN: 2395-0072
© 2017, IRJET | Impact Factor value: 5.181 | ISO 9001:2008 Certified Journal | Page 1363
Fig 3. Sequence Diagram
VII. ADVANTAGES
There are a number of advantages like:
[1] We can cross check how much fuel is
deposited.
[2] We can also check where we have deposited
fuel.
[3] Instant Notification.
. VIII. CONCLUSIONS
The proposed system will make sure that how much
amount of fuel is exactly deposited to avoid loss of
amount of money. System implementation will be done
by using flow sensor and mobile .We can get good
mileage.
IX. REFERENCES
[1] Albarbar, A., Fengshou Gu, and A. D. Ball.
"Diesel engine fuelinjection monitoring using
acoustic measurements and independent
component analysis." Measurement 43.10
(2010): 1376-1386.
[2] Kum, Dongsuk, Huei Peng, and Norman K
Bucknor. "Optimal energy and catalyst
temperature management of plug-in hybrid
electric vehicles for minimum fuel consumption
and tail-pipe emissions." IEEE Transactions on
Control Systems Technology 21.1
[3] Tie, Siang Fui, and Chee Wei Tan. "A review of
energy sources and energy management system
in electric vehicles." Renewable and Sustainable
Energy Reviews 20 (2013): 82-102.
[4] Basu, Debraj, et al. "Wireless sensor network
based smart home: Sensor selection, deployment
and monitoring." Sensors Applications
Symposium (SAS), 2013 IEEE. IEEE, 2013.48
(SAS), 2013 sIEEE. IEEE, 2013.](https://image.slidesharecdn.com/irjet-v4i2266-171120064613/85/IOT-based-fuel-monitoring-for-future-vehicles-3-320.jpg)
IOT based fuel monitoring for future vehicles.
- 1. International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395 -0056 Volume: 04 Issue: 02 | Feb -2017 www.irjet.net p-ISSN: 2395-0072 © 2017, IRJET | Impact Factor value: 5.181 | ISO 9001:2008 Certified Journal | Page 1361 IOT BASED FUEL MONITORING FOR FUTURE VEHICLES. Prof.J.N.Nandimath,Varsha Alekar, Sayali Joshi, Sonal Bhite, Pradnya Chaudhari. Department Of Computer Engineering STES, Smt Kashibai Navale College Of Engineering, Pune Savitribai Phule Pune University -----------------------------------------------------------------------***-------------------------------------------------------------------------------------- Abstract—In today's world, actual record of fuel filled and fuel consumption in vehicles is not maintained. It results in a financial loss. To avoid this we are implementing an IOT fuel monitoring and tracking system. We can use the reed switch which works according to the principle of Hall Effect for sensing the amount of fuel filled in the vehicle. So as soon as agent starts filling petrol in your bike/car, the flow sensor is activated. This flow sensor will be active till flow ends. Once flow ends it will calculate the amount of fuel filled and directly notify on your mobile phone. If the phone is not available then it will store this data on cloud. Keywords: Reed Switch, Flow Sensor ,IoT ,Flow rate, Tail pipe emission. I. INTRODUCTION Flow sensor is typically output of pulses proportional to the instantaneous flow rate which means that to interpret them it is necessary to implement simple frequency counter. Since this project uses a fuel flow sensor containing a Hall Effect sensor that output a pulse rate proportional to flow rate, so not only it is a useful project in its own right but it also demonstrates a very useful technique that you can use in a wide range of projects that need to measure the rate at which something happens (an electronic wind instrument, for example). Flow rate can be determined by different techniques like change in velocity or kinetic energy. Here we have determined flow rate by change in velocity of fuel. Velocity depends on the pressure that forces the through pipelines. As the pipes cross-sectional area is known and remains constant, the average velocity is an indication of the flow rate. The basis relationship for determining the liquid flow rate in such cases is Q=V x A, where Q is flow rate/total flow of fuel through the pipe, V is average velocity of the flow and A is the cross-sectional area of the pipe (viscosity, density and the friction of the liquid in contact with the pipe also influence the flow rate of fuel). • Pulse frequency (Hz) = 7.5Q, Q is flow rate in Litres/minute • Flow Rate (Litres/hour) = (Pulse frequency x 60 min) / 7.5Q In other words: • Sensor Frequency (Hz) = 7.5 * Q (Litres/min) • litres = Q * time elapsed (seconds) / 60 (seconds/minute) • litres = (Frequency (Pulses/second) / 7.5) * time elapsed(seconds)/60 • litres = Pulses / (7.5 * 60) Once the flow started, application will start reading pulses and convert it into litres and then send to cloud server. Mobile application will also track location where fuel has been deposited. Fig 1. Flow Sensor II. RELATED WORK [1] Optimal Energy and Catalyst Temperature Management of Plug-in Hybrid Electric Vehicles for Minimum Fuel Consumption and Tail-Pipe Emissions. In this paper, they develop a method to synthesize a supervisory power-train controller (SPC) that achieves near-optimal fuel economy and tail pipe emissions under known travel distances. We first find the globally optimal solution using the dynamic programming (DP) technique, which provides an optimal control policy and state trajectories. Based on the analysis of the
- 2. International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395 -0056 Volume: 04 Issue: 02 | Feb -2017 www.irjet.net p-ISSN: 2395-0072 © 2017, IRJET | Impact Factor value: 5.181 | ISO 9001:2008 Certified Journal | Page 1362 optimal state trajectories, a new variable energy-to-distance ratio (EDR), is introduced to quantify the level of battery, state-of charge (SOC) relative to the remaining distance. This variable plays an important role in adjusting both energy and catalyst thermal management strategies for PHEVs. A novel extraction method is developed to extract adjustable engine on/off ,gear-shift, and power-split strategies from the DP control policy over the entire state space. Based on the extracted results, an adaptive SPC that optimally adjusts the engine on/off , gear-shift, and power-split strategies under various EDR and catalyst temperature conditions was developed to achieve near- optimal fuel economy and emission performance. [2] Wireless sensor network based smart home: Sensor selection, deployment and monitoring. This paper details the installation and configuration of sensors in an elderly person's house a smart home in the making in a small city in New Zealand. The overall system is envisaged to use machine learning to analyze the data generated by the sensor nodes. The novelty of this project is that instead of setting up an artificial test bed of sensors within the University premises, the sensors have been installed in a subject's home so that data can be collected in a real not artificial environment. III. PROPOSED SYSYTEM The location history of individual fleet vehicles allows precisely time managed, current and forward journey planning, responsive to changing travelling conditions. To avoid this we are implementing an IOT fuel monitoring and tracking system. So as soon as some agent starts filling petrol in your bike/car the flow sensor activated. This flow sensor will be active till flow ends. Once flow ends it will calculate the amount of fuel filled and directly notify on yours mobile phone. IV.SYSTEM ARCHITECTURE: . The following figure gives a brief idea about the system architecture Fig 2. System architecture The location history of individual fleet vehicles allows precisely time managed current and forword journey planning ,responsive to changing travelling conditions. To avoid this we are implementing an IOT based fuel monitoring for future vehicles. When agent start filling petrol in your vehicle flow sensor will get activated. This sensor will active till the flow ends. Once the flow ends it will calculate how much amount of fuel is inserted and this information will directly notify on your mobile. Also location can track via GPS so we know from where we have deposited the fuel. V.PERFORMANCE REQUIREMENT [1] JVM should be tuned on mobile to provide extra address space to application. [2] Raspberry-pi 3 will be used. [3] Hardware should have 1 GB RAM and good processor. VI. FLOW SEQUENCE [1] Initially power get on and flow sensor get started. [2] Flow sensor will wait till flow of fuel get started. [3] Flow sensor will calculate how much amount of fuel is filled. [4] Then this calculated information of fuel is send to the cloud. [5] At the same time location is fetch by the users mobile.
- 3. International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395 -0056 Volume: 04 Issue: 02 | Feb -2017 www.irjet.net p-ISSN: 2395-0072 © 2017, IRJET | Impact Factor value: 5.181 | ISO 9001:2008 Certified Journal | Page 1363 Fig 3. Sequence Diagram VII. ADVANTAGES There are a number of advantages like: [1] We can cross check how much fuel is deposited. [2] We can also check where we have deposited fuel. [3] Instant Notification. . VIII. CONCLUSIONS The proposed system will make sure that how much amount of fuel is exactly deposited to avoid loss of amount of money. System implementation will be done by using flow sensor and mobile .We can get good mileage. IX. REFERENCES [1] Albarbar, A., Fengshou Gu, and A. D. Ball. "Diesel engine fuelinjection monitoring using acoustic measurements and independent component analysis." Measurement 43.10 (2010): 1376-1386. [2] Kum, Dongsuk, Huei Peng, and Norman K Bucknor. "Optimal energy and catalyst temperature management of plug-in hybrid electric vehicles for minimum fuel consumption and tail-pipe emissions." IEEE Transactions on Control Systems Technology 21.1 [3] Tie, Siang Fui, and Chee Wei Tan. "A review of energy sources and energy management system in electric vehicles." Renewable and Sustainable Energy Reviews 20 (2013): 82-102. [4] Basu, Debraj, et al. "Wireless sensor network based smart home: Sensor selection, deployment and monitoring." Sensors Applications Symposium (SAS), 2013 IEEE. IEEE, 2013.48 (SAS), 2013 sIEEE. IEEE, 2013.