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Research Paper

City cleanliness using geo-tagged images with experimental results

During the process of smart city construction, city planners and managers always spend a lot of energy and money for cleaning street garbage due to the random appearances of street garbage. Consequently, visual street cleanliness assessment is particularly important. However, the existing assessment approaches have some clear disadvantages, such as the collection of street garbage information is not automated and street cleanliness information is not real-time. To address these disadvantages, this paper proposes a novel urban street cleanliness assessment approach using mobile edge computing and deep learning. First, the high resolution cameras installed on vehicles collect the street images. Mobile edge servers are used to store and extract street image information temporarily. Second, these processed street data is transmitted to the cloud data centre for analysis through city networks. At the same time, Faster Region-Convolutional Neural Network (Faster R-CNN) is used to identify the street garbage categories and count the number of garbage. Finally, the results are incorporated into the street cleanliness calculation framework to ultimately visualize the street cleanliness levels, which provides convenience for city managers to arrange clean-up personnel effectively. Index Terms— Smart cities, street cleaning, garbage detection, deep learning, mobile edge computing.

Published by: Krishna Sonawane, Prachi Pingle, Siddhant Lunawat, Trupti Zagade, Dr. Meenakshi Thalor

Author: Krishna Sonawane

Paper ID: V7I4-1285

Paper Status: published

Published: July 12, 2021

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Research Paper

AI-based chatbots for providing health-related information

Chatbots in the health care systems may have the potential to provide patients with access to immediate medical information. Health care chatbots can help patients better manage their own health; improve access and timeliness to care. Al-based Chatbots for supplying health-related information. The System uses artificial intelligence which includes advanced Natural language processing to answer the query Tf-IDF weighting. The User can query any health-related activities through the system. The user does not have to personally go to the health for an inquiry. The software analyses the questions and then answers the user. The software answers the queries as if it is questioned by a person. The software answers using a Graphical user interface which implies that as if a pupil is talking to the user. The user has to register himself to the software and has to log in. After login user can access the bot. A chatbot is a program that communicates with people.

Published by: Dungi Pravalika Reddy, Dadala Shantha Shekinah, Gunisetty Pavani Suvarna Satya, Kolla Hasitha Naidu, Dr. K. Soumya

Author: Dungi Pravalika Reddy

Paper ID: V7I4-1326

Paper Status: published

Published: July 12, 2021

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Research Paper

Size-specific variation in the rate of oxygen consumption, ammonia excretion, and O: N ratio of freshwater bivalve lamellicorns marginalis during the season of monsoon

Malacology means the study of molluscan animals and also conchology means the study of the molluscan shell. Body mass is one of the best known and most studied characteristics of aquatic animals on scaling of metabolic rates. We studied here how size-specific variation in the rate of oxygen consumption, ammonia excretion, and O: N ratio in Freshwater Bivalve Mollusc Lamellidens marginalis species in an attempt to know how size-specific variation affects their metabolism. The freshwater bivalve molluscs were chosen for experimental work from Bhima River at Siddhatek in August and September for the period of monsoon season with body size i.e. small (75-79 mm in shell-length) and large (90-93 mm in shell-length). In current work reported that the rate of oxygen consumption and O: N ratio was high in the small body-sized bivalve mollusc but the rate of ammonia excretion was low in small body-sized bivalves compared to large ones. The results are discussed in the flush of metabolic processes in fresh-water bivalve molluscs.

Published by: Pritesh Ramanlal Gugale

Author: Pritesh Ramanlal Gugale

Paper ID: V7I4-1320

Paper Status: published

Published: July 12, 2021

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Research Paper

Helping business owners to find potential competitors

Opening a business in any place is not an easy task as it needs lots of things to be considered. One should consider its competitors before opening a business. This project is one attempt to help those business people to find their competitors. In this project, a taco palace is planned to open in the city of Monterrey, Mexico. Here the attempt is to find a neighborhood with not too many competitors with enough customers. To find the neighborhood, considering the latitude and longitude values of the city of Monterrey, Mexico, and can be able to locate the best place to open the restaurant. In this project Foursquare API is used to explore the neighborhoods and get the most common restaurants near that place and using this function clusters can be grouped. For clustering, a K-means clustering algorithm is used. Clusters are used to know the similar business in that areas. Clusters group the similar business and list out all its names. To visualize the neighborhoods Folium library is used.

Published by: Suraksha S. S., Darunya B. C., Priya D., Anisha B. S.

Author: Suraksha S. S.

Paper ID: V7I4-1279

Paper Status: published

Published: July 12, 2021

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Research Paper

Social Cause Marketing (Pink Capitalism) and its impact on consumers’ brand preferences

As its name implies, cause-based marketing is the process of marketing a specific idea, cause, or goal, rather than a specific business, product, or service. These initiatives are often partnerships between a nonprofit organization – typically the driving force behind the” “messaging of the campaign itself – and either an ad agency or corporate partner, which typically handles the execution of the campaign. Although cause-based marketing campaigns can focus predominantly on PPC or social advertising, these campaigns can and often do incorporate” elements of guerilla marketing in their execution. Trying to grab people’s attention is no easy feat these days, and as such many organizations adopt more creative ways of getting their message out, as we’ll see later on. Many cause-based marketing campaigns are organic offshoots of grassroots marketing efforts, which also tend to focus on causes. This paper will discuss thoroughly cause-related marketing through the lenses of Pink Capitalism. It will also discuss how pink capitalism is not entirely an ethically incorrect concept and focus on the silver lining of the same, which would benefit both the NGO as well as the corporations.

Published by: Saniya Savant

Author: Saniya Savant

Paper ID: V7I4-1276

Paper Status: published

Published: July 12, 2021

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Research Paper

Development of a home security Robot using Deep Learning and IoT

The major problem in every urban city is the lack of security to residential areas. The number of thefts, electricity and food wastage at homes in urban areas increase every year due to human error. As per the National Crime Records Bureau (NCRB), 2,44,119 cases of robbery, theft, and burglary took place in residential premises in 2019. Also, electricity consumption in Indian homes has tripled since 2010. In 2019, an urban Indian household consumed about 90 units (kWh) of electricity as a monthly average which is one-third of the monthly world average. To solve these issues, we have proposed an idea of a “Home Security Robot” for a smart city using AI. The Home Security Robot will help in eliminating the reliance on security guards and will effectively monitor everything in the house (if there are any gas leakage, fridge malfunctions, unnecessary electricity wastage, indoor air quality and any unknown movements inside the house). If the owner is under attack, he/she can shout out “HELP” or “SAVE ME "so that the robot can take in the voice command to automatically call the police. The navigation part is done by Arduino and Bluetooth RC Controller App. There are 2 parts (Face Detection & Recognition using Raspberry Pi and IoT system using BOLT module with sensors). The first part has three python programs used for facial detection and recognition using OpenCV with Haar Cascade Classifier and LBPH algorithm. The first program (Face Dataset) is used for collecting images of known users and storing it in a database using Haar Cascade Classifier. The second program (Face Training) is used to train the stored images using LBPH algorithm so the model can distinguish between the users whose faces are stored in database and then these trained images are stored in the trainer.yml file. The third program (Face Recognition) is used to read the trained images stored in the trainer.yml file and then uses Haar Cascade Classifier to recognize the detected face and identifies whether the face belongs to a user or an intruder. The IoT system with the help of BOLT module helps in checking the temperature in the room and checking if any unnecessary lights are on in the room. If the room temperature is outside the safe range specified or if any lights are on, owner will get an alert via SMS.

Published by: Shravan Aruljothi, Sharad Dewanand Parate, Harshit S., Nehal Dinesh Andani

Author: Shravan Aruljothi

Paper ID: V7I4-1269

Paper Status: published

Published: July 12, 2021

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