Human-centred methods for design of mobile social technologies : a case study of agile ridesharing

Social contexts are possible information sources that can foster connections between mobile application users, but they are also minefields of privacy concerns and have great potential for misinterpretation. This research establishes a framework for guiding the design of context-aware mobile social applications from a socio-technical perspective. Agile ridesharing was chosen as the test domain for the research because its success relies upon effectively connecting people through mobile technologies.

Formal analysis of card-based payment systems in mobile devices

To provide card holder authentication while they are conducting an electronic transaction using mobile devices, VISA and MasterCard independently proposed two electronic payment protocols: Visa 3D Secure and MasterCard Secure Code. The protocols use pre-registered passwords to provide card holder authentication and Secure Socket Layer/ Transport Layer Security (SSL/TLS) for data confidentiality over wired networks and Wireless Transport Layer Security (WTLS) between a wireless device and a Wireless Application Protocol (WAP) gateway. The paper presents our analysis of security properties in the proposed protocols using formal method tools: Casper and FDR2. We also highlight issues concerning payment security in the proposed protocols.

Global reconfiguration of a team of networked mobile robots among obstacles

This paper presents a full system demonstration of dynamic sensorbased reconfiguration of a networked robot team. Robots sense obstacles in their environment locally and dynamically adapt their global geometric configuration to conform to an abstract goal shape. We present a novel two-layer planning and control algorithm for team reconfiguration that is decentralised and assumes local (neighbour-to-neighbour) communication only. The approach is designed to be resource-efficient and we show experiments using a team of nine mobile robots with modest computation, communication, and sensing. The robots use acoustic beacons for localisation and can sense obstacles in their local neighbourhood using IR sensors. Our results demonstrate globally-specified reconfiguration from local information in a real robot network, and highlight limitations of standard mesh networks in implementing decentralised algorithms.

Food talks back : Exploring the role of mobile applications in reducing domestic food wastage

Mitigating domestic food waste reduces its environmental and economic impacts. In our study, we have identified the use of mobile technology to support behaviour change as a key tool to assist the process of reducing food waste. This paper reports on three mobile applications designed to reduce domestic food waste: Fridge Pal, LeftoverSwap and EatChaFood. The paper examines how each app can influence consumer knowledge of domestic food supply, location, and literacy. We discuss our findings with respect to three considerations: (i) assisting with the user’s food supply and location knowledge; (ii) improving the user’s food literacy; (iii) facilitating social food sharing of excess food. We present new insights for mobile interventions that encourage changes towards more sustainable behaviours to reduce food waste.

Acceptability-based QoE management for user-centric mobile video delivery : a field study evaluation

Effective Quality of Experience (QoE) management for mobile video delivery – to optimize overall user experience while adapting to heterogeneous use contexts – is still a big challenge to date. This paper proposes a mobile video delivery system to emphasize the use of acceptability as the main indicator of QoE to manage the end-to-end factors in delivering mobile video services. The first contribution is a novel framework for user-centric mobile video system that is based on acceptability-based QoE (A-QoE) prediction models, which were derived from comprehensive subjective studies. The second contribution is results from a field study that evaluates the user experience of the proposed system during realistic usage circumstances, addressing the impacts of perceived video quality, loading speed, interest in content, viewing locations, network bandwidth, display devices, and different video coding approaches, including region-of-interest (ROI) enhancement and center zooming

Bi-modal biometric authentication on mobile phones in challenging conditions

This paper examines the issue of face, speaker and bi-modal authentication in mobile environments when there is significant condition mismatch. We introduce this mismatch by enrolling client models on high quality biometric samples obtained on a laptop computer and authenticating them on lower quality biometric samples acquired with a mobile phone. To perform these experiments we develop three novel authentication protocols for the large publicly available MOBIO database. We evaluate state-of-the-art face, speaker and bi-modal authentication techniques and show that inter-session variability modelling using Gaussian mixture models provides a consistently robust system for face, speaker and bi-modal authentication. It is also shown that multi-algorithm fusion provides a consistent performance improvement for face, speaker and bi-modal authentication. Using this bi-modal multi-algorithm system we derive a state-of-the-art authentication system that obtains a half total error rate of 6.3% and 1.9% for Female and Male trials, respectively.

Place categorization and semantic mapping on a mobile robot

In this paper we focus on the challenging problem of place categorization and semantic mapping on a robot with-out environment-specific training. Motivated by their ongoing success in various visual recognition tasks, we build our system upon a state-of-the-art convolutional network. We overcome its closed-set limitations by complementing the network with a series of one-vs-all classifiers that can learn to recognize new semantic classes online. Prior domain knowledge is incorporated by embedding the classification system into a Bayesian filter framework that also ensures temporal coherence. We evaluate the classification accuracy of the system on a robot that maps a variety of places on our campus in real-time. We show how semantic information can boost robotic object detection performance and how the semantic map can be used to modulate the robot’s behaviour during navigation tasks. The system is made available to the community as a ROS module.

Consumer appraisals of mobile marketing communications

This paper reports on a study that investigates the emotions elicited from appraising SMS-based mobile marketing (m-marketing) communications under three marketing conditions: product consistency, incentives and permission giving. Results from the experimental design show that appraising m-marketing communications elicits both single emotions and mixed emotions; that is, a mixture of positive and negative emotions in the same response. Additionally, the results show that the influence of specific marketing conditions may increase or reduce the intensity of the emotions elicited. This study contributes to marketing practice by examining consumer appraisals of m-marketing communications under different combinations of marketing conditions. The results provide insights into which emotions are likely to be elicited as a result, and how a specific marketing condition might influence their levels of intensity. The study contributes to marketing theory also through combining appraisal theory with Richins (1997) consumption emotion set.