Android Applications for Automation Purposes

In recent years, the number of network-enabled smartphones everywhere has been increasing fast. With the rapid expansion of the Internet, people have been trying to reduce manual intervention as much as possible. A variety of sensors are embedded in today’s smartphones which make interfacing with the outside world, easy. The majority of the smartphone users have Android as the operating system. So in the world of smartphone Android has the largest platform as compared to other operating systems. So in this project work Android is used to automate some of the simple day to day manual activities. The thesis represents the design and development of simple android applications which are used to automate simple tasks. All the applications are compatible with Android 2.1 onwards. The designs of the proposed applications are on top of a Web interface which uses RESTful API as the communication protocol between client applications and web service. The applications take much advantage of sensors and techniques pre-installed in Android smartphones. The proposed applications follow optimizations according to the best practices recommended by Google, to increase user experience and reduce power consumption. The first one is PVSys, an Android application which gives the details of equipment required for solar pump installation at user’s backyard or a full solar panel installation at user’s house. The second one is BizCard, which automates the task of storing user’s business cards in digital form and retrieving the contacts when required. The third application, Auto Attendance Manager, automates the task of taking attendance for the teachers and lecturers without the aid of any external device. The Auto Attendance Manager can be integrated easily with the present application of the Institute.Automation of simple things with Android becomes easy. Moreover, a layman can work on Android interface since it is easy to implement and design the layouts. In today’s world when every device is trying to communicate its information to the internet, Android interface with Bluetooth or Wi-Fi can be used for the sam

Internet of Things-Based Smart Classroom Environment

Internet of Things (IoT) is a novel paradigm that is gaining ground in the Computer Science field. There’s no doubt that IoT will make our lives easier with the advent of smart thermostats, medical wearable devices, connected vending machines and others. One important research direction in IoT is Resource Management Systems (RMS). In the current state of RMS research, very few studies were able to take advantage of indoor localization which can be very valuable, especially in the context of smart classrooms. For example, indoor localization can be used to dynamically generate seat map of students in a classroom. Indoor localization is not the only concept which was not thoroughly researched in RMS. Another valuable proposition is to treat physical chairs as “smart” devices, which can report their occupancy, user information, and duration of presence to a cloud data store. Interconnected smart chairs consisting of pressure sensors, RFID readers, wireless communication capabilities, indoor localization and useful mobile application can serve as a powerful tool for instructors and other stakeholders. In this thesis we propose a complete smart classroom system consisting of smart chairs, anchor nodes, cloud storage and Android application. Implementation of indoor localization is a challenging and intricate task. Furthermore, since GPS chips cannot be used indoors, different and more challenging techniques have to be used. We developed a special protocol to handle communication and data flow of localization between smart chairs and the master node. Finally, the system was evaluated and special algorithm was developed to improve the accuracy of indoor localization in the context of smart classroom

Development and Impact of a Mobile Application that Allows Users to Track Their Location on an Educational Institution Campus

This research study aims to solve user location issues within the campus at an educational institution. As this campus comprises a large number of places and departments, users often get confused about how to reach a specific location. To address this problem, the “Ubícate” (“locate by yourself” in Spanish) application was developed following the CDIO methodology, which encompasses four creative process steps: conceive, design, implement, and operate. The “Ubícate” app provides users with information on places of interest such as schools, departments, halls, auditoriums, and sports venues, offering a visual reference of available locations through 360-degree images. The application also uses Google Maps to track user location within the campus, thus marking a reference route between university gates and the different locations available, in addition to providing information on university-sponsored events. In this paper, Section 2 describes the methodology and each of the stages that were addressed in the following sections. Section 3 presents the development itself and the data used for the purposes thereof. Next, Section 4 reveals the results from this study. Later, Section 5 assesses these results and the findings from the study. In Section 6, our conclusions are discussed. Finally, Section 7 lists topics for future research. The application did indeed contribute to improving the attendance of the academic community at events. Where the application was used, the first-hand perception of visitors and their own was very positive and enhanced the institutional image and sense of belonging. The contribution of this study consists of presenting a mobile application as a solution from three approaches: the technical aspects for application development, the business vision to satisfy the user’s needs, and the end user’s perception. All three approaches provide a technical reader, an entrepreneur, or an end user an overview of a scalable solution to different types of implementations in different types of businesses that require indoor location through the use of technologies in mobile applications. The mobile application performs the location indoors using the Google Maps platform, allowing a more agile development in implementing the APP

A tourism overcrowding sensor using multiple radio techniques detection

The motivation for this dissertation came from the touristic pressure felt in the historic neighborhoods of Lisbon. This pressure is the result of the rise in the number of touristic arrivals and the proliferation of local accommodation. To mitigate this problem the research project in which this dissertation is inserted aims to disperse the pressure felt by routing the tourists to more sustainable locations and locations that are not crowded. The goal of this dissertation is then to develop a crowding sensor to detect, in real-time, the number of persons in its vicinity by detecting how many smartphones it observes in its readings. The proposed solution aims to detect the wireless trace elements generated by the normal usage of smartphones. The technologies in which the sensor will detect devices are Wi-Fi, Bluetooth and the mobile network. For testing the results gathered by the sensor we developed a prototype that was deployed on our campus and in a museum, during an event with strong attendance. The data gathered was stored in a time-series database and a data visualization tool was used to interpret the results. The overall conclusions of this dissertation are that it is possible to build a sensor that detects nearby devices thereby allowing to detect overcrowding situations. The prototype built allows to detect crowd mobility patterns. The composition of technologies and identity unification are topics deserving future research.A motivação para a presente dissertação surgiu da pressão turística sentida nos bairros históricos de Lisboa. Esta pressão é a consequência de um crescimento do número de turistas e de uma cada vez maior utilização e proliferação do alojamento local. Para mitigar este problema o projeto de investigação em que esta dissertação está inserida pretende dispersar os turistas por locais sustentáveis e que não estejam sobrelotados. O objetivo desta dissertação é o de desenvolver um sensor que consiga detetar, em tempo real, detetar quantas pessoas estão na sua proximidade com base nos smartphones que consegue detetar. A solução proposta tem como objetivo detetar os traços gerados pela normal utilização de um smartphone. As tecnologias nas quais o sensor deteta traços de utilização são Wi-Fi, Bluetooth e a rede móvel. Para realizar os testes ao sensor, foi desenvolvido um protótipo que foi instalado no campus e num museu durante um evento de grande afluência. Os dados provenientes destes testes foram guardados numa base de dados de séries temporais e analisados usando uma ferramenta de visualização de dados. As conclusões obtidas nesta dissertação são que é possível criar um sensor capaz de detetar dispositivos na sua proximidade e detetar situações de sobrelotação/apinhamento. O protótipo contruído permite detectar padrões de mobilidade de multidões. A composição de tecnologias e a unificação de identidade são problemas que requerem investigação futura

Smart Room Attendance Monitoring and Location Tracking with iBeacon Technology

The objective of this project was to develop a system and a phone application using iBeacon technology to track people’s attendance and location at different types of events. This includes tracking their location by using a location algorithm and receiving identifying information from each person through the use of a phone application. This information will then be sent to a server for record keeping

Evaluating Sensor Data in the Context of Mobile Crowdsensing

With the recent rise of the Internet of Things the prevalence of mobile sensors in our daily life experienced a huge surge. Mobile crowdsensing (MCS) is a new emerging paradigm that realizes the utility and ubiquity of smartphones and more precisely their incorporated smart sensors. By using the mobile phones and data of ordinary citizens, many problems have to be solved when designing an MCS-application. What data is needed in order to obtain the wanted results? Should the calculations be executed locally or on a server? How can the quality of data be improved? How can the data best be evaluated? These problems are addressed by the design of a streamlined approach of how to create an MCS-application while having all these problems in mind. In order to design this approach, an exhaustive literature research on existing MCS-applications was done and to validate this approach a new application was designed with its help. The procedure of designing and implementing this application went smoothly and thus shows the applicability of the approach

Internet of Things. Information Processing in an Increasingly Connected World

This open access book constitutes the refereed post-conference proceedings of the First IFIP International Cross-Domain Conference on Internet of Things, IFIPIoT 2018, held at the 24th IFIP World Computer Congress, WCC 2018, in Poznan, Poland, in September 2018. The 12 full papers presented were carefully reviewed and selected from 24 submissions. Also included in this volume are 4 WCC 2018 plenary contributions, an invited talk and a position paper from the IFIP domain committee on IoT. The papers cover a wide range of topics from a technology to a business perspective and include among others hardware, software and management aspects, process innovation, privacy, power consumption, architecture, applications

Localization and Counting of Indoor Populations on a University Campus using Wi-Fi Connection Logs and Floor Plans

The localization and counting of persons in indoor spaces is an area of extensive research. Indoor population metrics can inform energy conservation, health and safety, security, resource optimization, and location-aware services such as marketing and navigation. Building utility is impacted by the number of persons in each space, and the management of person flows into and out of building spaces is a critical consideration of space design, and the COVID-19 pandemic elevated the need to accurately measure and monitor indoor populations. Indoor populations’ size, movement and location can be ascertained by a variety of automatic means, but scalability, repeatability and cost are limiting factors. One low-cost technique is the use of wireless logs from Wi-Fi-enabled devices, which provide precise counts but inaccurate locations due to Access Points’ widely varying coverage areas. Population locations, as estimated by wireless logs, are usually defined at a floor, or building level. In this paper, I propose a generalized technique for more precise identification of indoor populations’ location, using wireless logs. It is based on the merging of connection logs with floor layout plans, to define floor zones, representing the general area(s) of wireless coverage provided by each wireless AP, including areas served by more than one AP. The combined information allows for more precise location and counting of indoor populations. This analysis could be useful across multiple functional domains, including sustainability management, resource optimization, and capacity monitoring. The technique can be implemented in any environment where there is an extensive wireless network, widespread usage of the network, and reliable data records. It is non-invasive and does not require the purchase or installation of new equipment. As a case study, we applied the technique to data from a mid-sized university. Spatial and temporal population analyses were completed using wireless logs collected over a 6-week period prior to the COVID pandemic. The logs included unique User Ids and Device Ids; The floor layout plans included the installed locations of AP devices. Facilities management records included building, floor, and room metrics. Population analyses were completed by building, room types, work weeks, and duration of wireless connections. The population estimations for size and location were compared to expected indoor populations, based on student class enrolments and employee work schedules, to gauge accuracy and utility. Linear Correlation Coefficients were calculated for measured vs. expected population counts. The results indicated that the definition of Building Floor Zones provided more accurate indoor population location values than floor-level estimates, across a variety of building types and room types. Facilities management definitions for Building Floors allowed generic description of campus spaces that could be applied to any environment with varying building usage and occupant activity. The merged data allowed the estimation of indoor populations’ size and location at various levels of aggregation: zones, floors, and buildings; and allows for comparisons of activity in similar environments in differing locations. Possible research and/or application areas include: the use of indoor spaces outside of business hours, occupancy/utility rates, and the measurement of indoor crowd densities

Smart campuses : extensive review of the last decade of research and current challenges

Novel intelligent systems to assist energy transition and improve sustainability can be deployed at different scales, ranging from a house to an entire region. University campuses are an interesting intermediate size (big enough to matter and small enough to be tractable) for research, development, test and training on the integration of smartness at all levels, which has led to the emergence of the concept of “smart campus” over the last few years. This review article proposes an extensive analysis of the scientific literature on smart campuses from the last decade (2010-2020). The 182 selected publications are distributed into seven categories of smartness: smart building, smart environment, smart mobility, smart living, smart people, smart governance and smart data. The main open questions and challenges regarding smart campuses are presented at the end of the review and deal with sustainability and energy transition, acceptability and ethics, learning models, open data policies and interoperability. The present work was carried out within the framework of the Energy Network of the Regional Leaders Summit (RLS-Energy) as part of its multilateral research efforts on smart region