The automobile industry is currently looking at the technology needed to move from today's original autonomous autos to a self-contained and safe driving solution. The automobile industry has been remarkably successful in producing reliable, safe, and affordable cars over the past century. Due to the significant progress made in computers and telecommunications, an autonomous car became a reality. In this regard, an android driver-less car is a vehicle that uses a combination of motors, software, and sensors to park cars between destinations without a human operator. To be fully autonomous, vehicles must be able to travel unmanned to a pre-determined destination on roads that are not fit for use. In this paper, the android controlled Arduino based intelligent car parking development stages and functionalities has been discussed. The motor system will be composed of the dc motors that run the car as well as the wheels and body of the car. The DC motor controls the circuit and a software driver.  The android application will drive the car forward, reverse, left, and right (stopping will be the absence of a forward or backward command).  It will do this by means of the software driver.  There is also one motor which holds the brake and release. The significance of this system is that it has a distinctiveness to control real cars in real-time with android applications including steering control, gear shifting, horn control, and engine on/off. It has a self-parking system in a narrow crowded system through the sensors reading the environment and with actuators, a car could be park itself. Finally, on enabling effective automobile safety and efficient automotive cars, some of the challenges are needed to be addressed (and to provide) useful suggestions for approval by car manufacturers, designers, policymakers, and regulatory bodies.

With the advent of online social media, such as articles, websites, blogs, messages, posts, news channels, and by and large web content has drastically changed the way individuals take a glimpse at different things around them. Today, it's an everyday practice for some individuals to read the news on the web. Sentiment analysis (also called opinion mining) alludes to the utilization of natural language processing, content investigation, and computational linguistics to distinguish and separate subjective data in source materials. Sentiment analysis is broadly applied to online reviews, news feeds and social networking for a wide variety of applications, ranging from marketing to client services. Sentiment analysis emphasizes on the classification of textual data into positive, negative and neutral categories. This research is an endeavor to the case study that calculates news polarity or emotions on different sports feeds which may influence changes in sports news development patterns. The interest of this approach is to generate various text analytics that computes feelings from all pertinent ongoing sports news accessible out in the public domain. The significance and application value of sentiment analysis of RSS feeds in this study is to distinguish between positive feeds and negative feeds on sports that could affect readers or users minds in order to improve RSS feeds messaging broadcast among folks. The methodology utilizes the sentiment analysis techniques using two different online open-source sentiment analysis tools in Rich Site Summary (RSS) news feeds that have an influence on sports-related broadcast esteems.