Yeshwanth Krishna Kolli

Bio: Yeshwanth Krishna Kolli is an academic researcher from National Institute of Technology, Warangal. The author has contributed to research in topics: Water conservation & Water resources. The author has an hindex of 2, co-authored 2 publications receiving 40 citations.

Low cost smart parking system for smart cities

Abstract: Nowadays the idea of Smart Cities had become very popular. With the advent of Internet of Things, the concept of smart cities can be readily achievable. An extensive research is ongoing in the field of Internet of Things to increase the quality of services offered in cities and to improve the productivity and reliability of urban infrastructure. Internet of Things is addressing the most common problems faced in cities like availability of car parking and traffic jams. This paper presents an Internet of Things based Parking system for Smart Cities. The proposed parking system contains an IoT module deployed on-site for managing the available parking spaces. A platform provided in the form of portal for booking the parking spaces.

Waste water management for smart cities

Abstract: Water is a key resource for life on earth. Clean Drinking water is one of essential human needs. With the increase in urbanization a threat of water scarcity is alarming. This triggers the idea of reuse and recycling of waste water. This paper presents the need for waste water treatment and also gives the brief description of various stages of waste water treatment. The waste water treatment plan works optimally only under certain parameters. Hence sensors can be used at different stages of water treatment for automation. This paper presents the importance and necessity to recycle the waste water and provides a solution for automation of the waste water treatment plant.

Open-Source Electronics Platforms as Enabling Technologies for Smart Cities: Recent Developments and Perspectives

Abstract: With the increasing availability of affordable open-source embedded hardware platforms, the development of low-cost programmable devices for uncountable tasks has accelerated in recent years. In this sense, the large development community that is being created around popular platforms is also contributing to the construction of Internet of Things applications, which can ultimately support the maturation of the smart-cities era. Popular platforms such as Raspberry Pi, BeagleBoard and Arduino come as single-board open-source platforms that have enough computational power for different types of smart-city applications, while keeping affordable prices and encompassing many programming libraries and useful hardware extensions. As a result, smart-city solutions based on such platforms are becoming common and the surveying of recent research in this area can support a better understanding of this scenario, as presented in this article. Moreover, discussions about the continuous developments in these platforms can also indicate promising perspectives when using these boards as key elements to build smart cities.

Survey of Smart Parking Systems

Abstract: The large number of vehicles constantly seeking access to congested areas in cities means that finding a public parking place is often difficult and causes problems for drivers and citizens alike. In this context, strategies that guide vehicles from one point to another, looking for the most optimal path, are needed. Most contributions in the literature are routing strategies that take into account different criteria to select the optimal route required to find a parking space. This paper aims to identify the types of smart parking systems (SPS) that are available today, as well as investigate the kinds of vehicle detection techniques (VDT) they have and the algorithms or other methods they employ, in order to analyze where the development of these systems is at today. To do this, a survey of 274 publications from January 2012 to December 2019 was conducted. The survey considered four principal features: SPS types reported in the literature, the kinds of VDT used in these SPS, the algorithms or methods they implement, and the stage of development at which they are. Based on a search and extraction of results methodology, this work was able to effectively obtain the current state of the research area. In addition, the exhaustive study of the studies analyzed allowed for a discussion to be established concerning the main difficulties, as well as the gaps and open problems detected for the SPS. The results shown in this study may provide a base for future research on the subject.

IoT Based Smart Parking System for Large Parking Lot

Abstract: Car parking issue is a major contributor and has been yet a noteworthy issue with limited parking spots in urban communities. In this paper we present an IoT based smart parking system for large parking lot that can be used to efficiently manage the parking system by providing information on the nearest parking slot available through the mobile application and thereby reducing the congestion of parking seekers. In order to efficiently manage the parking system, a successful cloud-based smart parking system solution using the Internet of Things technology is been developed to guide the user to the nearest parking spot available.

Contactless Technologies for Smart Cities: Big Data, IoT, and Cloud Infrastructures

Abstract: Intelligent systems are enhancing city environments and improving their overall performance in all possible aspects. Innovations in the field of information and communication technologies (ICT) and the proliferation of big data, internet-of-things (IoT), and cloud (BIC) infrastructures revolutionize the existing agile city ecosystems while effectively addressing customers and citizens needs. In this paper, we address the technology-driven applications that are capable of influencing the existing city infrastructures during their transformation towards smart cities with contactless technologies. We present applications, design principles, technology standards, and cost-effective techniques that leverage BIC for contactless applications and discuss user interfaces deployed in smart city environments. We further discuss state-of-the-art sensing methods and smart applications that support cities with smart contactless features. Finally, a case study is reported on how BIC can assist in efficiently handling and managing emergency situations such as the COVID-19 pandemic.

An IoT Raspberry Pi-based parking management system for smart campus

Abstract: Parking slots have become a widespread problem in urban development. In this context, the growth of vehicles inside the university's campus is rapidly outpacing the available parking spots for students and staff as well. This issue can be mitigated by the introduction of parking management for the smart campus which targets to assist individually match drivers to vacant parking slots, saving time, enhance parking space utilization, decrease management costs, and alleviate traffic congestion. This paper develops an IoT Raspberry Pi-based parking management system (IoT-PiPMS) to help staff/students to easily find available parking spots with real-time vision and GPS coordinates, all by means of a smartphone application. Our system composes of Raspberry Pi 4 B+ (RPi) embedded computer, Pi camera module, GPS sensor, and ultrasonic sensors. In the IoT-PiPMS, RPi 4 B+ is used to gather and process data input from the sensors/camera, and the data is uploaded via Wi-Fi to the Blynk IoT server. Ultrasonic sensors and LEDs are exploited to detect the occupancy of the parking spots with the support of the Pi camera to ensure data accuracy. Besides, the GPS module is installed in the system to guide drivers to locate parking areas through the Blynk App. that discovers parking spaces availability over the Internet. The system prototype is fabricated and tested practically to prove its functionality and applicability. According to the results, the IoT-PiPMS can effectively monitor the occupancy of outdoor parking spaces in the smart campus environment, and its potency in terms of updating the data to the IoT server in real-time is also validated..