jntu k paper presentation

1. 4th International Conference on Computer
Vision, High Performance Computing, Smart
Devices and Networks (CHSN-2023)
Dr. Mohan Dholvan
Dr. Krishna Samalla
Dr. G. Narsimhulu
Paper ID: 72
Paper Title: Improving Safety and Air Quality in the Mining
Industry with IoT-Enabled Monitoring and Air
Purification Solutions

2. CONTENTS
 Abstract
 Introduction
 Literature survey
 Existing systems
 Proposed system
 Expected output
 Conclusion
 References

3. ABSTRACT
 The mining industry is very concerned about industrial safety. For workers to be safe and productive,
communication and healthcare are essential. To monitor and react to potential dangers, reliable
communication is essential, while medical personal protective equipment and examinations are crucial. The
mining industry has to improve safety measures because the existing safety systems have flaws. To minimize
dangers and safeguard workers, the mining industry uses safety systems like ventilation, emergency response
plans, and gas monitoring. Fresh air is provided via ventilation, dangerous gasses are detected by gas
monitoring, and accidents are reduced by emergency action procedures.
 These systems have drawbacks, including the inability to detect all gasses, in- sufficient airflow, and a
limited ability to reduce accidents. Therefore, these systems need to be improved. By enhancing
communication and utilizing the IoT (Internet of Things) to monitor air quality, toxicity, and workers’ vital
signs, our solution increases safety in the mining industry.
 Real-time monitoring and reporting of dangers is made possible via sensors, an esp32 board, and the Blynk
software. By keeping a close eye on vital signs, the aim is to promote well-being among workers and
enhance safety within the mining industry. Our suggested system significantly contributes to improving
safety in the mining industry by utilizing cutting-edge technology and creative solutions.

4. INTRODUCTION
 Industrial safety is one of the main aspects of the industry, especially the mining
industry. In the mining industry safety is a very vital factor. To avoid any types of
unwanted phenomena the mining industry follows some basic precautions and
phenomena.
 Communication and miner health care is the main key factor for any industry today to
monitor different parameters and take necessary actions accordingly to avoid any types
of hazards.
 To increase both safety and productivity in mines, reliable communication must be
established between workers and the base station.

5. LITERATURE SURVEY
 In 1995, a review paper [Chellappa et al. 1995] gave a thorough survey of FRT at that
time. (An earlier survey [Samal and Iyengar 1992] appeared in 1992.) At that time,
video-based face recognition was still in a nascent stage.
 During the past 8 years, face recognition has received increased attention and has
advanced ACM Computing Surveys, Vol. 35, No. 4, December 2003. Face Recognition:
A Literature Survey 403 technically. Many commercial systems for still face recognition
are now available.
 Recently, significant research efforts have been focused on video-based face
modeling/tracking, recognition, and system integration. New datasets have been created
and evaluations of recognition techniques using these databases have been carried out.

6.  In 2019 Priya Singh , Milad Sukram Suryawanshi and Dharshana Tak had published a paper
known as “Smart Fleet Management System Using IoT ” in 5th International Conference
For Covergence In Technology(I2CT).
 The objective of this paper was to present the effective use of niche technologies in solving
most critical problems of Fleet Industry.
 Jeo-joon Chung and Hyun-Jung Kim published an article “An Automobile Environment
Detection System Based on Deep Neural Network and its Implementation Using IoT –
Enabled In- Vehicle Air Quality Sensors” on 21 March 2020.
 This paper elucidates the development of a deep learning–based driver assistant that can
prevent driving accidents arising from drowsiness.
 Multimodal signals are collected by the assistant using five sensors that measure the levels of
CO, CO2, and particulate matter (PM), as well as the temperature and humidity.
 These signals are then transmitted to a server via the Internet of Things, and a deep neural
network utilizes this information to analyze the air quality in the vehicle.

7. EXISTING METHODOLOGY
 The existing systems contain basic wired communication systems which are not that
effective.
 As per the existing systems the communication range is less and their would be high
latancey while communicating.
 The safety measures for the worker are very basic as well as they can only purify least
amount of toxic air.
 Drawbacks of the existing system are :-
 Improper safety measures.
 Less effective communication system.

8. BLOCK DIAGRAM OF EXISTING SYSTEM
Figure 1:Existing System Block Diagram

9. PROPOSED SYSTEM
 Trying to improve the communication between the mine worker and the
base station.
 Measuring the air quality and the toxicity present in the air.(also
measure the humidity and temperature of the surroundings)
 Monitoring the pulse, and blood oxygen ratio of the worker.
 Providing oxygen in case of emergency.

10. BLOCK DIAGRAM PROPOSED MODEL
Figure 2:- Proposed Model Block Diagram

11. MODEL DESIGN
Figure 3:- 3D Model
Figure 4:- Blynk Output
Figure 5:- Output

12. RESULTS
 Measuring the air quality accurately.
 Purifying the air efficiently.
 Maintaining the effective communication range.
 Monitoring the blood oxygen levels of the worker.
 Updating the conditions to the base station

13. CONCLUSION
 Purification of air with 99% efficiency.
 Detection of all impurities and organic and inorganic pollutants.
 Sending exact location to the management hub when the driver
triggers emergency trigger.
 Maintaining the good communication between the worker and the
base station.

14. REFERENCES
1. Ms Menaga “Air Quality Monitoring System Using Vehicles Based on the IOT”.
https://www.irjet.net/volume-6- issue03, 2019.
2. Mr Xue Dong “Design of a filtering car air purifier”. In: www.iopscience.iop.org.
https://iopscience.iop.org/article/10.1088/1755-1315/632/5/052095, 2021.
3. H. Mengtao and F. Zunxiang, "Automobile Exhaust Purification System Research Based
on ARM," 2016 International Symposium on Computer, Consumer and Control (IS3C),
Xi'an, China, 2016, pp. 728-731, doi: 10.1109/IS3C.2016.186.
4. Meghana P Gowda, Harshitha G Y, Jyothi K N, Srushti, Padma R, “Air Quality
Monitoring System”, International Journal of Engineering Research & Technology
(IJERT) NCCDS – 2021 (Volume 09 – Issue 12).
5. Farih Bin Deraman, Asrudin Bin Mat Ali, Normi Bin Muhamad, "Innovation of air
quality detector in passenger car using IoT" Vol. 1, No. 1, 2020, pp. 16-20 Vol. 1, No. 1,
2020.

15. 6. https://robu.in/mq-series-gas-sensor/
7. https://www.electronicwings.com/
8. https://robocraze.com/blogs/post/what-is-pulse-sensor
9. https://cowaymega.com/blogs/blog/what-is-a-hepa-filter
10. https://www.indiancrusaders.com/blog/importance-of-activated-carbon-filter-in-an-air-
purifier/
11. https://www.electronicshub.org/getting-started-with-esp32/
12. https://techexplorations.com/guides/blynk/1-what-is-%20blynk
13. https://www.elprocus.com/lcd-16x2-pin-configuration-and-its-working/