scholarly journals AN IMPROVED SAFETY ALGORITHM FOR ARTIFICIAL INTELLIGENCE ENABLED PROCESSORS IN SELF DRIVING CARS

2019 ◽  
Vol 2019 (2) ◽  
pp. 95-104 ◽  
Author(s):  
Dr. Samuel Manoharan
Keyword(s):  
Artificial Intelligence ◽  
Road Safety ◽  
Human Population ◽  
Environmental Issues ◽  
The Self ◽  
Driving Ability ◽  
Time Data ◽  
The Road ◽  
The World ◽  
Self Driving Cars

The innovation in the automobiles have undergone a most noteworthy leap from the operation of the vehicles that was human centered to vehicles with the self –driving ability. The self-driving cars being a major level of attraction today, needs to concentrate also on the privacy, energy, traffic flow, environmental issues and the road safety. The perfect road safety is a goal that can be never achieved, due to the growing number of vehicles and the human population all over the world. Measures to improve the probability of the safety is put forward in the paper for the cars with the capability of the self-driving built with the artificial intelligence enabled processors. The performance evaluation of the proposed algorithm for using real time data ensures the competence of the safety algorithm in the self-driving cars.

Road Safety at Ghats using IoT

2021 ◽  
Vol 9 (VII) ◽  
pp. 132-136
Author(s):  
Alaparthi Maneesha
Keyword(s):  
Developing Countries ◽  
Cause Of Death ◽  
Road Safety ◽  
Led Light ◽  
The Road ◽  
The World

This paper describes how to overcome accidents at Ghat roads. In the developing countries accident is the major cause of death. If we look at the top 10 dangerous roads in the world we can see that all of them are mountain roads and curve roads. In the mountain roads there will be tight curves and the roads will be narrow. In these kinds of situations the driver of a vehicle cannot see vehicles coming from opposite side. Thousands of people lose their lives each year because of this problem. The solution to this problem is developing the Aurdino based project to provide safe and secure journey while travelling to the Ghat roads, Hill Stations, etc. It is provided by alerting the driver about the vehicle coming from opposite side. This is done by keeping a sensor in one side of the road before the curve and keeping a LED light after the curve, so that if vehicle comes from one end of the curve sensor senses and LED light glows at the opposite side. By looking at the LED light on/off criteria driver can become alert and can slow down the speed of the vehicle.

scholarly journals Synergistic Action of Immunotherapy and Nanotherapy against Cancer Patients Infected with SARS-CoV-2 and the Use of Artificial Intelligence

Cancers ◽  
2022 ◽  
Vol 14 (1) ◽  
pp. 213
Author(s):  
Tanvi Gupta ◽  
Tilahun Ayane Debele ◽  
Yu-Feng Wei ◽  
Anish Gupta ◽  
Mohd Murtaza ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Cancer Patients ◽  
Clinical Characteristics ◽  
Synergistic Action ◽  
Peak Time ◽  
Time Data ◽  
Major Threat ◽  
Vulnerable Patients ◽  
The World ◽  
Real Time Data

Since 2019, the SARS-CoV-2 pandemic has caused a huge chaos throughout the world and the major threat has been possessed by the immune-compromised individuals involving the cancer patients; their weakened immune response makes them vulnerable and susceptible to the virus. The oncologists as well as their patients are facing many problems for their treatment sessions as they need to postpone their surgery, chemotherapy, or radiotherapy. The approach that could be adopted especially for the cancer patients is the amalgamation of immunotherapy and nanotherapy which can reduce the burden on the healthcare at this peak time of the infection. There is also a need to predict or analyze the data of cancer patients who are at a severe risk of being exposed to an infection in order to reduce the mortality rate. The use of artificial intelligence (AI) could be incorporated where the real time data will be available to the physicians according to the different patient’s clinical characteristics and their past treatments. With this data, it will become easier for them to modify or replace the treatment to increase the efficacy against the infection. The combination of an immunotherapy and nanotherapy will be targeted to treat the cancer patients diagnosed with SARS-CoV-2 and the AI will act as icing on the cake to monitor, predict and analyze the data of the patients to improve the treatment regime for the most vulnerable patients.

scholarly journals Implementasi Algoritma K-Mean dalam Pengelompokan Data Kecelakaan di Kabupaten Kediri

2020 ◽  
Vol 1 (2) ◽  
pp. 53-60
Author(s):  
Adimas Ketut Nalendra ◽  
M. Mujiono ◽  
Rafika Akhsani ◽  
Adiguna Sasama Wahyu Utama
Keyword(s):  
Data Mining ◽  
Information System ◽  
Programming Languages ◽  
Human Population ◽  
The Road ◽  
Cluster Group ◽  
The World ◽  
On The Road ◽  
Minor Injuries ◽  
Motorized Vehicles

Abstract The increasing human population in the world with the need for mobilization of motorized vehicles both 2 wheels and 4 wheels is no longer a secondary need but has become a primary need. With the increasing population of vehicles on the road becoming its own problem that is often the occurrence of both single and successive accidents that resulted in many victims both minor injuries, severe to death. Kediri is one of the cities with high accident rates. Although in 2018 this number has decreased but in 2017 there were 1,258. This resulted in the need for an information system to dig deeper about it. The k-mean algorithm is an algorithm used to group the same data and put it into a Cluster group to dig up information. The information system was developed using PHP and MYSql programming languages. The results of clustering are of 3 types namely accident rarely, accident-prone and very accident-prone. The most common incidents in the Pare Subdistrict with the cluster being very accident-prone. Throughout 2017 pare sub-districts there were 133 accident cases. Keywords: K-Means, Data mining.,accident, PHP, clustering. __________________________ Abstrak Semakin meningkatnya populasi manusia di dunia dengan kebutuhan mobilisasi kendaraan bermontor baik roda 2 maupun roda 4 bukan lagi menjadi kebutuhan sekunder tetapi sudah menjadi kebutuhan primer. Dengan semakin meningkatnya populasi kendaraan di jalan raya menjadi maslah sendiri yakni sering terjadinya kecelakaan baik tunggal maupun beruntun yang mengakibatkan banyak korban baik luka ringan, berat sampai meninggal dunia. Kediri adalah salah satu kota yang masih tinggi angka kecelakaan. Meski di tahun 2018 ini mengalami angka penurunan akan tetapi di tahun 2017 tercatat 1.258. Hal ini mengakibatkan perlu adanya suatu system informasi untuk menggali lebih dalam mengenai hal tersebut. Algoritma k-mean adalah algoritma yang digunakan untuk mengelompokkan data yang sama dan dimaksukkan ke kelompok Cluster untuk menggali informasi. Pada system infprmasi dikembangkan menggunakan Bahasa pemograman PHP dan MYSql. Hasil dari clustering terdapat 3 jenis yaitu jarang terjadi kecelakaan, rawan kecekalaan dan sangat rawan kecelakaan. Kecataman dengan kejadian terbanyak terjadi di kecamatan Pare dengan cluster sangat rawan kecelakaan. Sepanjang tahun 2017 kecamatan pare terjadi kasus kecelakaan sebanyak 133 kasus. Kata Kunci: K-Means, Kecelakaan, Data mining, PHP, Clustering. __________________________

scholarly journals A PRELIMINARY STUDY ON UPDATING HIGH DEFINITION MAPS: DETECTING AND POSITIONING A TRAFFIC CONE BY USING A STEREO CAMERA

2019 ◽  
Vol XLII-4/W19 ◽  
pp. 271-274
Author(s):  
M. L. R. Lagahit ◽  
Y. H. Tseng
Keyword(s):  
Real Time ◽  
Data Storage ◽  
Autonomous Vehicles ◽  
Detection System ◽  
Time Data ◽  
High Definition ◽  
Stereo Camera ◽  
The Road ◽  
On The Road ◽  
Self Driving Cars

Abstract. The concept of Autonomous Vehicles (AV) or self-driving cars has been increasingly popular these past few years. As such, research and development of AVs have also escalated around the world. One of those researches is about High-Definition (HD) maps. HD Maps are basically very detailed maps that provide all the geometric and semantic information on the road, which helps the AV in positioning itself on the lanes as well as mapping objects and markings on the road. This research will focus on the early stages of updating said HD maps. The methodology mainly consists of (1) running YOLOv3, a real-time object detection system, on a photo taken from a stereo camera to detect the object of interest, in this case a traffic cone, (2) applying the theories of stereo-photogrammetry to determine the 3D coordinates of the traffic cone, and (3) executing all of it at the same time on a Python-based platform. Results have shown centimeter-level accuracy in terms of obtained distance and height of the detected traffic cone from the camera setup. In future works, observed coordinates can be uploaded to a database and then connected to an application for real-time data storage/management and interactive visualization.

The Significance of Time, Being and Transcendence on the Road to the Heideggerian Authentic Self

2020 ◽  
Vol 7 (2) ◽  
pp. 169-182
Author(s):  
Volkan Çifteci ◽  
Keyword(s):  
The Self ◽  
Authentic Self ◽  
The Road ◽  
The World ◽  
On The Road

This paper attempts to reveal the meaning of Heideggerian self on the basis of time. In the course of this, it examines Heidegger’s following terms: time, the self, the world and Being. In the present paper, the notions of anxiety, death, the call, freedom, transcendence, resolution and temporality (time) constitute a frame for articulating the meaning of the authenticity of Dasein. The road to the authentic self is challenging since it is not something already given; rather, the self is something to be accomplished. Dasein must accomplish it by making life its own. To achieve this, the elaboration of the meaning of “the Being of beings” in the exploration of Dasein must be the first step. For it is Dasein who can give an answer to the question of the meaning of “Being”.

Managing Human Resources in Artificial Intelligence Era 5.0

2022 ◽  
pp. 150-164
Author(s):  
Jyotsna Oswal ◽  
Namita Rajput ◽  
Sunny Seth
Keyword(s):  
Artificial Intelligence ◽  
Human Resources ◽  
The Road ◽  
The Past ◽  
Indian Context ◽  
The World ◽  
Effectiveness And Efficiency

Artificial intelligence (AI) has grown by leaps and bounds in the past few years making it a necessary tool for organizations all over the world to pave the road to a smart future by entering into its various functions and making it more efficient. However, companies in India have been hesitant and slow to adapt this technology, and this hesitation is ever so clearly seen in the human resources function of the organization. The primary purpose of this chapter is to explore the application, benefits and challenges of integration, and the limitations of AI in HRM within the Indian context. The study is relevant and beneficial to organisations that seek to enhance the effectiveness and efficiency of their HRM functions by leveraging the power of AI.

Screen-Camera-Cars

Film Studies ◽  
2019 ◽  
Vol 21 (1) ◽  
pp. 53-64
Author(s):  
Sonia Campanini
Keyword(s):  
Artificial Intelligence ◽  
Science Fiction ◽  
The Self ◽  
Human Interactions ◽  
Cinematic Narratives ◽  
Science Fiction Films ◽  
Self Driving Cars ◽  
Machine Interaction ◽  
Theoretical Considerations ◽  
Minority Report

Self-driving cars have long been depicted in cinematic narratives, across genres from science fiction films to fantasy films. In some cases, a self-driving car is personified as one of the main characters. This article examines cinematic representations and imaginaries in order to understand the development of the self-driving technology and its integration in contemporary societies, drawing on examples such as The Love Bug, Knight Rider, Minority Report and I, Robot. Conceptually and methodologically, the article combines close readings of films with technological concerns and theoretical considerations, in an attempt to grasp the entanglement of cinematographic imaginaries, audiovisual technologies, artificial intelligence and human interactions that characterise the introduction of self-driving cars in contemporary societies. The human–AI machine interaction is considered both on technological and theoretical levels. Issues of automation, agency and disengagement are traced in cinematic representations and tackled, calling into question the concepts of socio-technical assemblage.

scholarly journals Computational Sustainability and Artificial Intelligence in the Developing World

AI Magazine ◽  
2014 ◽  
Vol 35 (3) ◽  
pp. 36-47 ◽  
Author(s):  
John Quinn ◽  
Vanessa Frias-Martinez ◽  
Lakshminarayan Subramanian
Keyword(s):  
Artificial Intelligence ◽  
Natural Resources ◽  
Human Population ◽  
Developing World ◽  
Well Being ◽  
Developing Regions ◽  
Computational Sustainability ◽  
Management Of Resources ◽  
The World ◽  
Poor Management

The developing regions of the world contain most of the human population and the planet's natural resources, and hence are particularly important to the study of sustainability. Despite some difficult problems in such places, a period of enormous technology-driven change has created new opportunities to address poor management of resources and improve human well-being.

scholarly journals Machine Learning to Classify Driving Events Using Mobile Phone Sensors Data

2021 ◽  
Vol 15 (02) ◽  
pp. 124
Author(s):  
Yazan Alqudah ◽  
Belal Sababha ◽  
Esam Qaralleh ◽  
Tarek Yousseff
Keyword(s):  
Machine Learning ◽  
Road Safety ◽  
Autonomous Vehicles ◽  
Machine Learning Algorithms ◽  
Motion Sensors ◽  
The Road ◽  
Crowd Sensing ◽  
Innovative Solution ◽  
On The Road ◽  
Self Driving Cars

With the ever-increasing vehicle population and introduction of autonomous and self-driving cars, innovative research is needed to ensure safety and reliability on the road. This work introduces an innovative solution that aims at understanding vehicle behavior based on sensors data. The behavior is classified according to driving events. Understanding driving events can play a significant role in road safety and estimating the expense and risks of driving and consuming a vehicle. Rather than relying on the distance and time driven, driving events can provide a more accurate measure of vehicle driving consumption.  This measure will become more valuable as more autonomous vehicles and more ride sharing applications are introduced to roads around the world. Estimating driving events can also help better design the road infrastructure to reduce energy consumption.  By sharing data from official vehicles and volunteers, crowd sensing can be used to better understand congestion and road safety. This work studies driving events and proposes using machine learning to classify these events into different categories. The acquired data is collected using embedded mobile device motion sensors and are used to train machine learning algorithms to classify the events.

scholarly journals THE ROAD SAFETY AT TURBO ROUNDABOUTS IN POLAND

2015 ◽  
Vol 33 (1) ◽  
pp. 57-67 ◽  
Author(s):  
Elżbieta Macioszek
Keyword(s):  
Road Safety ◽  
The Other ◽  
Continuous Line ◽  
The Road ◽  
Traffic Lane ◽  
The World ◽  
High Level ◽  
Traffic Organization

There are to two groups of turbo roundabouts used currently in Poland. The first group is turbo roundabouts with geometry and traffic organization designed following the model of Dutch turbo roundabouts with raised lane dividers. The other group is turbo roundabouts with traffic organization which entirely or partly corresponds to traffic organization of conventional turbo roundabouts, but with lane dividers not present, with their function performed by a single continuous line of P-2 type. Turbo roundabouts in the world are considered as solutions which are characterized by a high level of road safety and allow for effective flow at substantial traffic intensities. The data about turbo roundabouts in Poland analysed by the author show that there are substantially more turbo roundabouts without raised lane dividers. The paper attempts to answer to the question of whether turbo roundabouts with lane dividers in the form of a single continuous line ensure the appropriate level of road safety. Furthermore, the comparison of the level of road safety in turbo roundabouts equipped in raised lane dividers with turbo roundabouts with lane separators in the form of continuous line revealed that turbo roundabouts with raised lane dividers are safer solutions than turbo roundabouts with traffic lane dividers in the form of continuous line.

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