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.

Abstract-In this project, mobile connectivity and an innovative approach to sensor data gathering and integration have been employed to automate maintenance inspection, performance monitoring and ride quality measurement in vertical transportation systems. An Inertial Navigation System (INS) has been proposed, implemented and tested to track lift car movement profile. The inherent characteristics of vertical motion have been used to minimize errors and obtain higher accuracy in the integration results. The measurement of a correlation between kinematic profiles constructed from lift-car tracking data compared to its nominal values provides key information on the lift condition at any time. A frequency analysis was applied to processing vibrations and noise data, effectively adding another dimension to the lift ride quality measurement. This approach enabled lift performance profiles to be compiled automatically and transmitted in real time, which significantly rationalized and improved the process of maintenance inspection and monitoring. An advanced prototype, AdInspect, has been produced, with the full set of described features. Industry partners are currently evaluating it.