Barriers to Socio-economic Opportunities in Africa: An e-Government Perspective

Various barriers to socio-economic opportunities in Africa are explored though e-Government as a lens of study. Using grounded theory methodology, scholarly literature on e-Government in Africa has been analyzed to model various barriers. The research is expected to serve as a scholarly reference for decision-makers in the private and the public sector organizations, as well as policymakers, for making decisions about design, development and execution of e-Government initiatives in Africa

Addressing data collection challenges in ICT for development projects

This paper equips researchers for addressing a wide range of data collection challenges experienced when interacting with marginalized communities as part of ICT4D projects in developing countries. This secondary research categorizes data collection challenges reported in multiple disciplines, and summarizes the guidance from the past literature to deal with the challenges. The open, axial, and selective coding of data collection challenges reported by the past literature suggests that it is necessary to manage scope, time, cost, quality, human resources, communication, and risks for addressing the data collection challenges. This paper illustrates the ways to manage these seven dimensions using (a) the success stories of data collection in the past, (b) the lessons learned by researchers during data collection as documented by the past literature, and (c) the advice they offer for collection data from marginalized communities in developing countries

Beyond Access to Information: Understanding the Use of Information by Poor Female Mobile Users in Rural India

Digital inclusion research has focused overwhelmingly on access to information. But access to information by itself is of limited value unless the intended beneficiary has the capacity to use it. It is the use of information that delivers the benefits. However, in ICT for development literature, there is little empirical work on the process by which use of information delivers benefits. This study fills the gap by studying information use by poor female mobile phone users in rural India. It identifies six stages in the information use process and models them

Applying information science lens for advancing critical research on IT adoption: Insights from continued usage of mobile phones by poor women in rural India

Critical research on IT adoption dominated by cognitive models grounded in psychology and communication is always in search of new theoretical perspectives to understand, explain, and interpret social issues. Since information plays an important role in IT adoption, this study applies an information science lens to investi-gate the factors affecting the continued usage of mobile phones in rural India. Analysis of interviews with 22 women earning less than a dollar day reveals the influence of social, economic, cognitive, technological, and information-related factors on their continued usage of mobiles. Micro- and meso-level socioeconomic motives and active information-seeking behavior emerge as the most significant factors encouraging respondents to continue using mobiles against several technical and human barriers. The application of information science lens yields three constructs and ten micro-, meso-, and macro-level variables, advancing critical research on IT adoption with the help of a theoretical lens outside of psychology and communication literature

Inequalities creating economic barriers to owning mobile phones in India: Factors responsible for the gender digital divide

In India, men own around 70% of mobile phones, creating a gender digital divide for the most widely owned information and communication technology (ICT) in the world. This study investigates the factors responsible for the inability of 245 female slum-dwellers in India earning less than $2 a day to own a mobile phone. Open, axial and selective coding of survey responses shows that socio-cultural, economic, demographic, psychological, communication-related, and health related inequalities in the lives of the respondents create eight economic barriers precluding respondents from owning some of the least expensive mobile phones worth$15 or so on installments of $1 a month

POSE ESTIMATION AND 3D RECONSTRUCTION USING SENSOR FUSION

A camera maps 3-dimensional (3D) world space to a 2-dimensional (2D) image space. In the process it loses the depth information, i.e., the distance from the camera focal point to the imaged objects. It is impossible to recover this information from a single image. However, by using two or more images from different viewing angles this information can be recovered, which in turn can be used to obtain the pose (position and orientation) of the camera. Using this pose, a 3D reconstruction of imaged objects in the world can be computed. Numerous algorithms have been proposed and implemented to solve the above problem; these algorithms are commonly called Structure from Motion (SfM). State-of-the-art SfM techniques have been shown to give promising results. However, unlike a Global Positioning System (GPS) or an Inertial Measurement Unit (IMU) which directly give the position and orientation respectively, the camera system estimates it after implementing SfM as mentioned above. This makes the pose obtained from a camera highly sensitive to the images captured and other effects, such as low lighting conditions, poor focus or improper viewing angles. In some applications, for example, an Unmanned Aerial Vehicle (UAV) inspecting a bridge or a robot mapping an environment using Simultaneous Localization and Mapping (SLAM), it is often difficult to capture images with ideal conditions. This report examines the use of SfM methods in such applications and the role of combining multiple sensors, viz., sensor fusion, to achieve more accurate and usable position and reconstruction information. This project investigates the role of sensor fusion in accurately estimating the pose of a camera for the application of 3D reconstruction of a scene. The first set of experiments is conducted in a motion capture room. These results are assumed as ground truth in order to evaluate the strengths and weaknesses of each sensor and to map their coordinate systems. Then a number of scenarios are targeted where SfM fails. The pose estimates obtained from SfM are replaced by those obtained from other sensors and the 3D reconstruction is completed. Quantitative and qualitative comparisons are made between the 3D reconstruction obtained by using only a camera versus that obtained by using the camera along with a LIDAR and/or an IMU. Additionally, the project also works towards the performance issue faced while handling large data sets of high-resolution images by implementing the system on the Superior high performance computing cluster at Michigan Technological University