14th IEEE International Conference on Open-Source Systems and Technologies (ICOSST-2020) goes virtual in Pandemic. KICS, UET Lahore positions as a Resource Centre for Islamic World in the ICT domain

ICOSST is a flagship event of Al- Khawarizmi Institute of Computer Science (KICS), UET Lahore that has been happening successfully at the institute since 2006. Like every year, this year’s conference was unique in its features that inspired researchers, academics, Industrial experts, Public sector and private organizations not only from across the country but also from across the globe to witness quality research papers, invited talks, panel discussion and 3D modeled virtual exposition. This year’s conference was somehow different in COVID’19 perspective, to keep face to face interaction minimal it was organized virtually using CISCO powered online conferencing tool i.e., WebEx. The option to attend from home and ease of access led to a surge in participation. This year’s conference brought another good news as on the same day KICS, UET Lahore was announced as a Resource Centre for the Islamic world in the ICT domain by Higher Education Commission (HEC) and Islamic Development Bank (IDB). Launching event for the report on ‘Mapping Pakistan’s resources centers” happened online where the President of Islamic Development Bank (IsDB), H.E Dr. Bandar Hajjar, Minister of Economic Affairs, Pakistan (IsDB Governor), H.E Makhdum Khusro Bakhtyar and Executive Director, Higher Education Commission of Pakistan, Dr.Shaista Sohail graced the occasion with their welcoming remarks. Representatives from various resource centers in Agriculture, Agro-based industries, Pharmaceuticals, Information, and communication technologies participated zealously in their respective sessions. Director KICS, Prof. Dr. Waqar Mahmood presented what KICS has been doing in the area of ICT that enabled the center to achieve excellence.

The Governor Punjab, H.E. Chaudhry Muhammad Sarwar graced the opening ceremony of ICOSST-2020 with his presence as a Chief Guest. Minister for Higher Education, Government of Punjab, H.E. Raja Yasir Humayon Sarfraz and Chairman Punjab Higher Education Commission, Prof. Dr. Fazal Ahmad Khalid were invited as Distinguished Guests. Vice-Chancellor UET Lahore, Prof. Dr. Syed Mansoor Sarwar welcomed the honorable guests, invited speakers, industrial experts, and public and private institutes on their participation and also appreciated Dr. Waqar Mahmood and his team for putting up a great show. Out of 176 research papers submitted from various countries including Pakistan.

India, China, Italy, Lebanon, USA, Bulgaria, Bangladesh, Indonesia, Saudi Arabia, South Korea, Philippine, and Nigeria, the Technical Evaluation Committee accepted 35 papers qualifying the merit-based criteria. Speakers were invited from prestigious universities of Pakistan and other countries like Italy, the United States, Amsterdam, Germany, and China to deliver talks in the areas of Network Security and IoT, Software and System, Cloud Computing and Big Data, Artificial Intelligence and COVID’19 pandemic. One of the prominent agendas of this year’s conference was to put forward strategies and innovative solutions to fight COVID’19 and based on this idea a panel discussion themed “Fighting COVID’19 through innovation’ was part of the ICOSST-2020. The distinguished panel comprised Dr. Adnan Jabbar, Mr. Meer Anwar, Mr. Omer Ghani, Dr. Hammad, and Dr. Zartash Uzmi.

“Showcasing industrial and academic projects in a digital environment was a challenging task” Dr. Waqar Mahmood, Director KICS, said while talking to the media officials. A virtual exposition was designed in a 3D environment where products from different research labs of KICS were displayed in such a manner that visitors could have live demos experience in a Virtual reality-based environment. The unique exposition organized using VR based technology not only attracted visitors but also set an example of organizing expositions in Pandemic. More than a dozen industries showcased their products in the exposition. Participating industries include ArhamSoft Pvt.Ltd, TechHive Solutions, Jolta Electric, Zoxcell, Desollnt. Pvt. Ltd, Silicon st, Grandeur Tech, Ebryx, Tower Technologies, Xeber, Repairwala.Pk, Tranchulas, ComSoft Solutions, ArbiSoft, Techverx, Global Technologies.

Duration: Self-paced 21 days (Recommended learning hrs: 6-hrs/week)

Dates: 28 Sept, 2020 to 19 Oct, 2020

Registration Deadline: 26th September 2020

Registration LinK: https://iioe.ichei.org/training  (Enrolment/Registration guide is attached)

Leading Instructor: Dr. Wen Zheng, Assistant Professor of the Department of Communications and Computer Engineering at Waseda University, Japan

Prospective Learners: Educators and professionals in higher education who wish to enhance data literacy and data analytic skills in their teaching and research

Recommended devices:  Participate in IIOE Training via desktop computers and laptops.

On Tuesday, September 15, 2020, NCAI associated Lab AGVRL_KICS_UETL organized a successful webinar by the name of ‘on Node deep Learning’, under the supervision of Dr. Usman Ghani Khan (PI_NCAI). A number of participants including NCAI associated labs i.e. AGVRL, CVML, and private software houses attended the webinar.

The key speaker of the webinar was Muhammad Ahmad Hassan (sr. research officer) AGVRL lab. In this session, he very clearly enlightens the concept of current paradigms of security and surveillance system, problems associated with traditional manual and automatic surveillance systems, current challenges to the CCTV security systems. Further, he also proposed the practical, applicable and reliable solution to all issues related to security and surveillance systems in on node deep learning.

Furthermore, in explanation with the current scenario, he said; our security systems are being shifted to cameras, thermo graphics cameras; video streams based authorization and detection, person authorization, object detection, and site surveillance. But here, the problem is, all this installation needs a force of human resources to monitor and process all the streamed data. That is quite a time-taking and of course, we cannot ignore the chances of human error.     

Here, he quoted the example of a safe city. There are almost ten thousand cameras that are continuously generating streams. Let’s if we apply the same concept of “Safe city” to all the provinces, it would be the required installation of almost fifty thousand cameras. These cameras would continuously generate live streams and producing tons of data. If this data is to be filtered, monitored, and processed by a human, it would take approximately ten thousand manpower and months of time. But still, after doing all that, human error and negligence cannot be ignored. As humans cannot pay attention consistently for a long period, he has desires and emotions too. These are unavoidable limitations of traditional security and surveillance systems.

Further limitations of hybrid security surveillance systems are;

1. Heavy servers required for video processing.
2. Central server dependency.
3. On Node decision.
4. Network delay.

In case of offline processing the limitations are;

1. Difficult to retain such Mammoth data.
2. Processing will incur resources.
3. Financial constraints.
4. Technical constraints.
5. Spatial constraints.

Solution for current surveillance challenges

Mr. Muhammad Ahmad Hassan proposed an authentic, reliable solution to all the above-mentioned problems. He also demonstrates the practical application in real time. That was noted and appreciated by all the attendees. According to his proposed solution,

1. If each node in the surveillance system work, process and make the decision individually then the system can easily tackle the above-mentioned challenges.
2. Processing and decision should be on the individual node and final results can easily be transmitted to the main server.

• Deep learning models can also be implemented if financially affordable. This can easily solve our system problems like; data storage, network delay and on node decision etc.

1. On Node deep learning-based automation can also help us to overcome all such problems. For this, we need to embed deep learning models on node.

Further, he also discusses in-depth about on Node processing devices. Some of them are;

Raspberry Pi4

FPGA (Sparten 3e)

NVidia Jetson  Nano

Mr. Muhammad Ahmad Hassan also discussed in detail the working model, functionality, and useful features of TensorRT. I.e. it provides high-performance inference in deep learning. It has low latency and high throughput. Its libraries are available in C++ and python. Most importantly, it is compatible with almost all the available framework of deep learning like;

1. Tensorflow
2. Keras
3. MxNet
4. Pytorch
5. Caffe etc.

The webinar was concluded with a number of live demos and answering the questions raised by the audience. Speaker tried to satisfy them all with comprehensive answers and examples.  All attendee was thankful of the institute for arranging such an advance and knowledge-rich webinar.