Applications of Deep Learning for Millimeter Wave: A Review

Millimeter Wave (mm-wave) has been considered as significant importance in various communication systems. It has achieved a greater attention to meet the capacity requirement of the future 5G network. Since mm-wave has a high frequency (30 to 300 GHz) using orthodox technologies for mm wave is more challenging. Thus advanced technology i.e. Deep Learning (DL) is a pragmatic approach to analyze a massive amount of data. Firstly, to find out how DL has beaten traditional approaches, this review briefly explores, the different methods of DL for mm wave are. Secondly, the review of the multiple applications in mm wave such as beam and blockages prediction, beam spacing, beamforming for mm wave OFDM system, precoding for mm-wave, channel estimation for mm-wave, sparse channel estimation, and hybrid precoding and fingerprinting-based indoor localization with mm wave is concisely explained. Last but not least, several studies have proved that DL has superior efficiency for mm wave than conventional approaches.

Shopick - Shop for ease

According to findings made during a survey performed at malls, consumers have difficulty determining their best preferences and requirements while shopping. Local marketers confront several obstacles. They don't have access to a platform that may aid in the expansion and growth of their sales and business. Following this statistic, Shopick was created, which would be beneficial to both customers and suppliers.

A Survey of Strategies, and Procedures for Detecting Drone Utilizing Sound, Radar, Thermal Infrared Sensor and Video Applications

With the exponential rise in the use of drones anywhere anytime, malicious use by outlaws is increasing as well. This calls for protective, detective, preventive measures to counter these attacks. This paper aims to review literature on drone detection and classification that utilizes a myriad of modalities ranging from using thermal infrared sensors to radar detections. In addition, there is a summary of a detailed discussion on drone classification along with recent progress and development in drone detection using machine learning, all of which is performed in an attempt to identify means to thwart such attacks. Furthermore, some future research directions, related to this new field of study, are discussed.

Journey of a Thousand Miles Begins with a Single Step: Transparity A Web-based Job Portal

Gender based discrimination is still common and one of the biggest issues in Pakistan. Transgender are ignored in almost every lifestyle. They face biasedness while finding for a job and are forced to earn money using unrespectable ways such as begging and dancing. Although, Pakistani law declares them equal citizen and many government as well as private organizations offer them jobs. Most of the transgender people remain unaware of these job offers due to the lack of an existing information propagation channel. This paper has proposed Transparity; which a dedicated online job portal for transgender. Transparity is also equipped with supportive features such as CV creation, online courses and motivational profiles to make it effective and helpful. Our study reveals that no such dedicated portal exists in Pakistan. This study focuses on the improvement of employment issues of transgender through.

The Role of Artificial Intelligence and Smart Classrooms during Covid-19 Pandemic and its impact on Education

Artificial Intelligence (AI) technology has revolutionized the education sector in terms of conducting classes. Especially during Covid-19 which affected significantly the education community resulting in the shift towards online learning rather than conventional classroom teaching. This study involves experiential learning during Covid-19 lockdown situation in the field of education, learning and teaching. It discusses how education practitioners can deal with Covid19 pandemic using the benefits of AI. AI innovation in education sector has contributed not only in education but also on human development. This research aims to identify the current situation of online classes and to propose a hybrid model of Education Management System (EMS) and Machine Learning (ML).

Smart Beef-Quality Tracking In Malaysia Using Blockchain Technology

Concerns and awareness on beef quality and safety are increasing among the consumers. Beef that is being served to the customers has to be of good quality and safe to eat, as well as to prevent foodborne illnesses. Hence, it is important to ensure good meat quality during the process of beef production. The existing beef supply chain systems lack transparency, as a result, a hike in food frauds has been witnessed in Malaysia. Consequently, it is hard to infer if the beef reaching the consumers is safe and wholesome. Besides that, the existing supply chains have a time-consuming and tiring procedure of product tracking, which is not desirable for consumers and other various stakeholders involved. To mitigate this issue, in this paper, we propose the use of blockchain technology for beef supply chain to maintain the transparency of ingredients and processes used in beef production. This will strengthen the trust of consumer in the company and ensure that the produced beef is contamination free and healthy. The study comprehensively highlights the feasibility blockchain technology to be implemented in the beef supply chain to make it transparent, secure and easily trackable.

Application of IoT for Power Controlling in Smart Home

The rapid growth in the population of major cities is causing an increase in energy consumption. Several approaches, including the use of recent technological advancements, are becoming increasingly important. IoT-based applications are becoming more common in addressing a variety of real-time issues. The central idea of the project in collaborating with this new technology is the human-machine interaction. Furthermore, the proposed architecture enables energy-saving applications that perform the following primary functions: estimating energy utilization of the home environment using metering devices; and applying user-defined limits that cut off boundaries providing if it exceeds energy limits. The Internet serves as an interactive medium between servers and home appliances, monitoring and controlling energy consumption remotely. For the purpose, android platform is used to design a mobile application. Raspberry Pi is dedicated for the server that maintains the database of each controllable unit. The proposed idea is successfully tested in the laboratory environment with synthetic load and in real-time over a running energy meter, to evaluate the efficiency and effectiveness.

Smart Safety Helmet for Safe Coal Mining

In any production and service industry, the safety of their workers/labors is very critical. The workers directly related with production are generally more prone to the threats because of their exposure to electro-mechanical, chemical, thermal, environmental, civil and other hazards. The coal mining industry in one of the most risky industries in terms of workers’ lives hazards. In the under-developed countries, any potential disaster in the underground mining turns into huge catastrophic losses of both the human lives and equipment. This paper presents some statistical data of mining disasters worldwide and propose an architecture for a smart helmet to be used by miners for their safe working inside the coalmines.

Design And Development Of Smart Parking Management System

The parking systems in the modern age are under tremendous stress as the number of vehicles on the roads are increasing every year. Due to this increase, the current parking lots do not suffice which leads to people driving for parking spaces thus wasting valuable time and adding to the greenhouse emissions. Therefore, new efficient and innovative solutions need to be developed which meets the ever- increasing demand for parking spaces and be as environmentally friendly as possible. The solution devised in this project is an enhancement of the current parking system with an integrated mobile application which allow drivers to remotely monitor parking lots, make reservation for a spot prior to visiting the parking lot and make in app payments for the parking services. This reduces the time spent in looking for parking spots as well as reduces the unnecessary carbon emissions while offering a practical and seamless parking experience to the users.

Factors Affecting The Usability Of Unstructured Big Data

Big data is a valuable asset for organisation as it analyses and help to understand the customers, changes within their business environment, market analysis and future trends. The big data is multifaceted (different data types and versatile), and mostly exists in unstructured formats. The extraction of value from this data is challenging. The usability and productivity of this multifaceted unstructured data is greatly compromised. A number of factors and associated reasons affect the usability of unstructured big data. The present research work investigates these factors and associated reasons behind the usability issues of multifaceted unstructured big data. The identification of these factors contribute to develop solutions to reduce the lack of usability of highly unstructured big data. A detailed study of existing literature followed by survey questionnaire has been conducted to identify the factors and their reasons. Descriptive statistics has been used to analyse and interpret the data and results.