M2SMART PROJECT

1M2SmartNewsLetter

Vol.7March 2020

M2SMART LAB AT IITH (JAN 2020)

JST MID TERM REVIEW AT IITH

JST Mid-Term Review at IITH
by Haruka Katarao, M2Smart Resident Coordinator

Showcasing M2Smart Project inHyderabad and Ahmedabad!
Japan Science and Technology Agency(JST) conducted the Mid-term review
for the M2Smart Porjcet at the Indian
Institute of Technology Hyderabad(IITH) on 27 January and in
Ahmedabad on 29 January 2020.

At the IITH, JST also conducted theon-sight visit of the IITH Test-bed andM2Smart Lab.
In Ahmedbad, M2Smart project
conducted Workshop and received theAhmedabad smart-city related
authorities and relevant institutions
members for showcasing the current
M2Smart Project in Hyderabad andAhmedabad.

JST Mid-Term Review

IITH Test-bed on sight visit

Ahmedabad Workshop

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Deep Learning-Based SmartParking Solution using Channel
State Information inLTE-based Cellular Networks
by Abhinav Kumar (Group 2) and Amala Sonny and Prabhat Kumar Rai

Amala Sonny is working on Development of a wireless signal based Smart Parking system in M2SMART project along with Mr.
Prabhat Kumar Rai. We are working with Dr. Abhinav Kumar. I presented a poster based on our work related at COMSNETS 2020,
held at Bangalore from 6th to 12th of January 2020. The title of the paper is “Deep Learning-Based Smart Parking Solution using
Channel State Information in LTE-based Cellular Networks”. In this work, we proposed a novel approach to detect and localize
cars in a parking area with the help of deep learning. The wireless data collected from the parking area is used to train the DL
model and the system will provide the real time location of cars and the vacant parking spaces available in the parking slot. Thesystem is more reliable and less complex as it does not need a transmitter. The data collection set up and the flow chart of theproposed system is given below.
Objectives:••

To find out the total number of cars present in the parking space.
To localize the position of the cars in the parking space.

Data Collection Set up:• The LTE downlink signal acquired using USRP B210 and VERT2450 antenna SDR platform.
• Operates on LTE passband frequency range of 2300MHz to 2400MHz.
• The data captured for different number of cars located at various positions in the parking space.
• All the processing is done using srsLTE software with C language.
System Flow Chart:

Numerical results are given in terms of accuracy.

2

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3

Study on Cyber-Security for IoT Edge Utilizing Pattern Match
Accelerator
by Hiroyuki Hosono (Group 1)

A malware detection algorithm that can be embedded in
IoT edge computing is proposed in this study andvalidated using an emulator. This algorithm, with apattern match accelerator, reduces the computing cost
while maintaining a relatively high detection accuracy.
For autonomous driving, complicated IoT edge
computing must have a huge amount of embedded
program codes. In such a situation, the invasion ofmalware can lead to compromised cybersecurity. In thisstudy, a pattern match accelerator is implemented forsuch issues, thereby offering IoT edge computing that
detects malware automatically. Edge computing isFig.1 Relationship of Statistics applied to Malware Analysis.

designed to apply simply structural level analysis algorithms using HLAC mask pattern (Fig.1). We developed a pseudo-emulator
system environment (Fig.2) and conducted performance confirmation of the proposed technique using 641 chosen samples fromsix types of malware families. The algorithm’s efficiencies demonstrated an identification performance of approximately 80%. In
comparison to characteristic extraction using AI, the computing cost was reduced and these processes enable edge computing
with high cybersecurity features.

Fig.2 a Pseudo-Emulator System

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4Publications
Conference poster presentation⚫

Amala Sonny, Prabhat Kumar Rai, Abhinav Kumar, Mohammed Zafar Ali Khan, “Deep Learning-Based Smart Parking Solutionusing Channel State Information in LTE-based Cellular Network”,09 March 2020.

JST Mid-Term Review in Ahmedabad Photo Gallery

M2SmartNewsLetterVol. 7March 2020

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