Distributed Sensor Logging: As Easy as a Mesh of Yoyos

This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.The Mass Gathering Data Acquisition and Analysis (MaGDAA) project involved the development of hardware and software solutions to facilitate the rapid and effective collection of autonomous and survey based data during mass gathering events. The aim of the project was the development and trial of a purpose-built Open Hardware based environment monitoring sensor prototypes using IOIO (pronounced “yoyo”) boards. Data from these sensors, and other devices, was collected using Open Source software running on Android powered mobile phones, tablets and other open hardware based platforms. Data was shared using a Wi-Fi mesh network based on an Open Source project called The Serval Project. Additional data in the form of survey based questionnaires were collected using ODK Collect, one of the applications in the Open Data Kit suite. The MaGDAA project demonstrated that it is possible for researchers (through the use of Open Source software and Open Hardware) to own, visualise, and share data without the difficulties of setting up and maintaining servers. MaGDAA proved to be an effective infrastructure independent sensor logging network that enables a broad range of data collection (demographic, predispositions, motivations, psychosocial and environmental influencers and modifiers of audience behaviour, cultural value) in the field of mass gathering research

Pengembangan Model Blood Mobile Collection Routing Problem (BMCRP) pada Proses Pengumpulan Darah

This research develop a model of blood mobile collection using blood donor vehicle efficiently by determining the optimal route of blood collection to the points of blood collection. The model developed in the form of mixed integer nonlinear programming (MINLP) and this model is called Blood Mobile Collection Routing Problem (BMCRP). The purpose of this model is to minimize the total distance of the blood collection routing process in which each place of blood collection has the opening hours and the closing time (time windows) and the service time in each place. This study considers the blood age (spoilage time) for 6 hours to ensure blood quality. The mathematical model is then verified to determine whether the solution is in accordance with the characteristics of BMCRP. Verification is done by solving Blood Mobile Collection Routing small cases. The simulation of solving BMCRP is done by generating eight hypothetical data sets of small cases based on vehicle routing data problems with different characteristics. Verification of BMCRP uses LINGO software. From the simulation results, the BMCRP model can obtain optimal solutions with minimum total distance travelled and does not violate any constraints on BMCRP

Pengembangan Model Blood Mobile Collection Routing Problem (BMCRP) pada Proses Pengumpulan Darah

This research develop a model of blood mobile collection using blood donor vehicle efficiently by determining the optimal route of blood collection to the points of blood collection. The model developed in the form of mixed integer nonlinear programming (MINLP) and this model is called Blood Mobile Collection Routing Problem (BMCRP). The purpose of this model is to minimize the total distance of the blood collection routing process in which each place of blood collection has the opening hours and the closing time (time windows) and the service time in each place. This study considers the blood age (spoilage time) for 6 hours to ensure blood quality. The mathematical model is then verified to determine whether the solution is in accordance with the characteristics of BMCRP. Verification is done by solving Blood Mobile Collection Routing small cases. The simulation of solving BMCRP is done by generating eight hypothetical data sets of small cases based on vehicle routing data problems with different characteristics. Verification of BMCRP uses LINGO software. From the simulation results, the BMCRP model can obtain optimal solutions with minimum total distance travelled and does not violate any constraints on BMCRP

Multiple multimodal mobile devices: Lessons learned from engineering lifelog solutions

For lifelogging, or the recording of one’s life history through digital means, to be successful, a range of separate multimodal mobile devices must be employed. These include smartphones such as the N95, the Microsoft SenseCam – a wearable passive photo capture device, or wearable biometric devices. Each collects a facet of the bigger picture, through, for example, personal digital photos, mobile messages and documents access history, but unfortunately, they operate independently and unaware of each other. This creates significant challenges for the practical application of these devices, the use and integration of their data and their operation by a user. In this chapter we discuss the software engineering challenges and their implications for individuals working on integration of data from multiple ubiquitous mobile devices drawing on our experiences working with such technology over the past several years for the development of integrated personal lifelogs. The chapter serves as an engineering guide to those considering working in the domain of lifelogging and more generally to those working with multiple multimodal devices and integration of their data

Using Technology Enabled Qualitative Research to Develop Products for the Social Good, An Overview

This paper discusses the potential benefits of the convergence of three recent trends for the design of socially beneficial products and services: the increasing application of qualitative research techniques in a wide range of disciplines, the rapid mainstreaming of social media and mobile technologies, and the emergence of software as a service. Presented is a scenario facilitating the complex data collection, analysis, storage, and reporting required for the qualitative research recommended for the task of designing relevant solutions to address needs of the underserved. A pilot study is used as a basis for describing the infrastructure and services required to realize this scenario. Implications for innovation of enhanced forms of qualitative research are presented

EpiCollect+: linking smartphones to web applications for complex data collection projects.

© 2014 Aanensen DM et al.Previously, we have described the development of the generic mobile phone data gathering tool, EpiCollect, and an associated web application, providing two-way communication between multiple data gatherers and a project database. This software only allows data collection on the phone using a single questionnaire form that is tailored to the needs of the user (including a single GPS point and photo per entry), whereas many applications require a more complex structure, allowing users to link a series of forms in a linear or branching hierarchy, along with the addition of any number of media types accessible from smartphones and/or tablet devices (e.g., GPS, photos, videos, sound clips and barcode scanning). A much enhanced version of EpiCollect has been developed (EpiCollect+). The individual data collection forms in EpiCollect+ provide more design complexity than the single form used in EpiCollect, and the software allows the generation of complex data collection projects through the ability to link many forms together in a linear (or branching) hierarchy. Furthermore, EpiCollect+ allows the collection of multiple media types as well as standard text fields, increased data validation and form logic. The entire process of setting up a complex mobile phone data collection project to the specification of a user (project and form definitions) can be undertaken at the EpiCollect+ website using a simple drag and drop procedure, with visualisation of the data gathered using Google Maps and charts at the project website. EpiCollect+ is suitable for situations where multiple users transmit complex data by mobile phone (or other Android devices) to a single project web database and is already being used for a range of field projects, particularly public health projects in sub-Saharan Africa. However, many uses can be envisaged from education, ecology and epidemiology to citizen science