Review on IoT Mobile App based on Rural Development in Terms of Agriculture

As India is still a developing country, it has a lot of rural areas wherein the living conditions and standards are below world standards and may even be on the underdeveloped scale of living standards. In order to achieve development in these regions the first and foremost step to initiate is to improve the agriculture standards and methodologies and bring in new technology to improve the methods used in agriculture which is the major source of income to these people. This project is a four staged project which intends on improving the agriculture standards of India. The first stage of the project is an automated humidity and moisture control for the soil, this will help the farmers in automating certain aspects and hence eliminate certain human errors and improve yield. The second stage of the project is an agriculture auction portal wherein the farmers can directly auction their products to the wholesaler without the need of a middle man/broker. The third stage of the project is an android app which conducts various surveys and suggests a new farmer the type of farming/seeds to be planted / soil information and other such relevant data in respect to agriculture which would help increase the yield for a new farmer. The last part of the project is a seed cum financial bank which helps the farmers by providing financial as well as seed aid in times of financial crisis.

Development of a Mobile Application to Buy Books through Visual Recognition

Mobile devices have become the most used tool for a large number of tasks that we regularly perform such as relating them, searching for information, and in particular for making purchases. A situation that is frequently repeated in many areas is discovering an object that belongs to another person but we would be interested in being able to acquire it. However, the problem arises of knowing where to buy it. For example, this happens with the clothes that other people are wearing. Today, technology offers recognition mechanisms that can help solve this problem. This article presents an Android app that can recognize a book based on an image and offer places where it can be purchased. For this, Google technology was used to recognize objects from images and it has been combined with the information provided by Google Books to find stores that sell recognized books. In this way, a system has been created that makes it easier for any user to identify and purchase books that they discover at any given time.

Accessibility Monitoring for People with Disabilities

The Accessibility for Ontarians with Disabilities Act (AODA) is a law mandating that organizations in Ontario must comply to accessibility standards for people with disabilities. However, there is no tool to report accessibility complaints and track them. To that effect, mobile applications can be effective to make report and monitor accessibility issues as they arise in private as well as public spaces (e.g. building, sidewalks). An App would provide users with an opportunity beyond the mapping of compliance, it can provide data that addresses the gaps across legislation and embodied experiences. The objective of this paper is to share a novel method associated with the development accessibility monitoring Android App prototype called “ACCESS-ABILITY.” ACCESS-ABILITY is a first-of-its-kind app in the domain of disability informatics, it facilitates the formation of a collaborative virtual community that can be used by people with disabilities, advocacy groups, organizations and official bodies.

Industrial Crane Automation Using Cloud with Artificial Intelligent and Machine Learning

This paper describes the design and development of a construction crane for use in lifting in the heavy weight object at construction site. The construction crane was developed by automatic system which was modified by adding the sensors like proxy sensors, pressure sensors and advance control system. The crane using 3 phase dc motors and voltage range of 220 to 650 volts. The cranes system is controlled through android app using an internet implementing adequate algorithms to ensure a smooth movement and prevent the undesired swinging effects. The machine is operated via a Man Machine Interface (MMI) installed in the android mobile. The range of crane control operations extended by using the internet of things (IOT).

Design and Analysis of Industrial Automation using Speech Recognition with Wireless Technology

Today, Internet is the best place to communicate and share information among the people throughout the world and gives an endless support of knowledge and entertainment. The main objective of Internet technology is to increase efficiency and decrease human effort. With the introduction of Internet of Things (IoT) in the last decade, we have been pushing for ubiquitous computing in all spheres of life. Physically challenged people are also using the Internet with the help of Speech commands (SC). The main objective of this paper is to minimize the effort and increase efficiency of the Voice recognition and IoT based secured automation, To design multi parameter monitoring system using Microcontroller that measures and controls various global parameters and the system comprises with wireless mode of communication. These processes were managed using Arduino and Bluetooth. The parameters that can be tracked are temperature, humidity and fire. Here we design the automatic system for voice based industrial automated system. That is an android app is used to give input data as voice input to the micro controller. In the micro controller section there will be a Bluetooth module to receive the data transmitted. Once the data is received the coding is executed according to the data which the controller got. Here we can monitor the temperature, humidity and gas and fire value of the industry and according to the values the prevention action is taken. The motor, dc fan and the light is turned on and off according to the voice input. And the action done here is implemented to the IOT.

KORELASI ADVERSITY QUOTIENT DENGAN PRESTASI NILAI SKOR TOSM PADA PENGURUS OSIS SMK

This study aims to empirically test the influence of adversity quotient on the achievement of ToSM (test of second mathematics) scores on the student. The hypothesis proposed is the influence of adversity quotient on the accomplishment of ToSM scores on students. The subjects in this study amounted to 34 students from SMK Negeri 1 Dukuhturi, Tegal Regency. The sampling technique used is saturated sampling. The measuring instruments in this study were adversity quotient scales and Android app-based ToSM. The results of this study showed the significance of the correlation test was 0.671 > 0.05 and Pearson correlation = 0.075 < r table = 0.3246, while the linearity test explained the magnitude of the correlation value / R relationship of 0.75 of the output obtained a coefficient of determination (R Square) of 0.006, which contains the understanding that the influence of Adversity Qutotien variable on variable performance ToSM score value is 0.6%, the data can be interpreted that there is no correlation between the variables studied, these findings can also be interpreted that to increase KHDI is not enough just by relying on adversity intelligence alone need other efforts.

Researching the Links between Smartphone Behavior and Adolescent Wellbeing: The Study Protocol for the FUTURE (WP4) Ecological Momentary Assessment Study (Preprint)

BACKGROUND Smartphone ownership has increased among teens within the last decade, with up to 89% of adolescents owning a smartphone and through it engaging daily with the online world. Although the results of recent meta-analyses suggest that engaging digital technology plays only a small role in adolescent wellbeing, parents, professionals, and policy makers remain concerned about the impact that the instant connectivity of smartphones has on adolescent wellbeing. OBJECTIVE Herein, we introduce the protocol of a research study investigating the associations between adolescent smartphone use and different facets of well-being (social, physical, psychological) that aims to apply innovative methods to address limitations of existing empirical studies. METHODS This 12-month prospective study of adolescents uses a repeated measurement-burst design with Ecological Momentary Assessment (EMA) methodology. Adolescents (N=203; age range 13-17) complete baseline assessments through online questionnaires, four 14-day intensive data collection bursts, and an online questionnaire at the end of the study. As part of the four measurement bursts, adolescent smartphone behavior is assessed objectively by passive data collection of smartphone data logs and through self-reports in short questionnaires administered via a custom-built Android app. RESULTS The protocol describes the study objectives, research tools (including the development of the Android app and specialized software) and process (including pilot studies the main study, and targets for machine learning approaches). The design of the study will allow for the assessment of both within- and between-person variability in smartphone behavior, as well as short-term variation and long-term change in smartphone behavior and how it impacts indicators of social, physical, and psychological wellbeing. Preliminary analyses of the data from the first data collection burst of the main study indicate acceptable level of compliance (72.25%) with the daily questionnaires. CONCLUSIONS The innovative methods applied in this study (objective smartphone logs, EMA, machine learning) will allow for a more nuanced assessment of the links between smartphone use and wellbeing, informing strategies to help adolescents navigate the online world more constructively in terms of the development of their physical, social and psychological wellbeing.

Identification of Fraud Apps Using Sentiment Analysis Techniques

Considering that application’s security is an important aspect, especially nowadays with the increase in technology and the number of fraudsters. It should be noted that determining the security of an application is a difficult task, especially since most fraudsters have become skilled and professional at manipulating people and stealing their sensitive data. Therefore, we pay attention to spot insecure apps by analyzing user feedback on Google Play platform using sentiment analysis. As it is known, user reviews reflect their experiments and experiences in addition to their feelings and satisfaction with the application. But unfortunately, not all of these reviews are real, fake reviews do not reflect the sincerity of feelings, so we have been keen in our work to filter the reviews and deliver accurate and correct results. This tool is useful for both users wanting to install an android app and for developers interested in app’s optimization.