In our daily life, it is difficult to meet financial demand while in crisis. This financial crisis may be solved with financial assistance from the banks. The financial assistance is nothing but... Show More

In our daily life, it is difficult to meet financial demand while in crisis. This financial crisis may be solved with financial assistance from the banks. The financial assistance is nothing but availing loan from the bank with proper agreement to repay the amount including calculated interest within the loan approved tenure. The customer can only avail loans against the submission of some valid and important supportive documents. However, although the customer is aware of the whole process of repayment and installment along with loan approval tenure, most of the time it is hard to get the approved loan within a shorter period. Therefore, the objective of this paper is to automate this manual and long process by predicting the chance of approval of the loan. The novelty of this research article is to apply machine learning techniques and classification algorithms to predict loan eligibility through an automatic online loan application process

This paper examines the new viewpoints that have evolved as a result of the advent of internet of things (IoT) in the kitchen. Companies are now exploring how internal knowledge and skillsets relate... Show More

This paper examines the new viewpoints that have evolved as a result of the advent of internet of things (IoT) in the kitchen. Companies are now exploring how internal knowledge and skillsets relate to the new technical needs that evolving digital environment entails; and they are learning more about IoT and connected products going through internal research. Accordingly, they hope to rely on the internet of things to keep kitchens safe. Cooking leads to cause of house fires and fire injuries. The bulk of the fires in the building started in the kitchens of the units. Three elements are required to start and maintain a fire. The human body is made up of these three elements: fuel, heat, and oxygen. Fire safety measures includes protect building from damage and death. An IoT-based system detects CO2 and Methane (CH4) levels in the environment and kitchen, as well as temperature. It has the ability to prevent accidents and save lives and property. When sensor data is synced, an IoT-based controlling device sends notifications to the mobile phones of the chosen number set in the alert section.

Detection of humans in flames is a challenging task. The task in this work is classified into two stages. The first is detection of fire, and the second is detection of human. The proposed method... Show More

Detection of humans in flames is a challenging task. The task in this work is classified into two stages. The first is detection of fire, and the second is detection of human. The proposed method involves fire detection based on colour format YCbCr for image preprocessing. It further uses a histogram of oriented gradient (HOG) and support vector machine (SVM) to detect a human in the fire. It evaluates several motion-based feature sets for human detection in the form of videos. In this work, both modules were integrated to make them work together. For the detection of fire, four different rules involving colour thresholding were used and background differencing was used for moving object detection. The main objective of this work is to spot the humans in the flames who are trapped in it so they can be rescued quickly. This can help the firefighters in rapid planning and serious zone detection. The proposed model has 81% efficiency, which has outperformed the existing models for detection of humans in flames.

Object detection is used in almost every real-world application such as autonomous traversal, visual system, face detection, and even more. This paper aims at applying object detection technique to... Show More

Object detection is used in almost every real-world application such as autonomous traversal, visual system, face detection, and even more. This paper aims at applying object detection technique to assist visually impaired people. It helps visually impaired people to know about the objects around them to enable them to walk free. A prototype has been implemented on a Raspberry PI3 using OpenCV libraries, and satisfactory performance is achieved. In this paper, a detailed review has been carried out on object detection using region-conventional neural network (RCNN)-based learning systems for a real-world application. This paper explores the various process of detecting objects using various object detections methods and walks through detection including a deep neural network for SSD implemented using Caffee model.