Obstacle avoidance routing scheme through optimal sink movement for home monitoring and mobile robotic consumer devices

In recent years, ZigBee has been proven to be an excellent solution to create scalable and flexible home automation networks. In a home automation network, consumer devices typically collect data from a home monitoring environment and then transmit the data to an end user through multi-hop communication without the need for any human intervention. However, due to the presence of typical obstacles in a home environment, error-free reception may not be possible, particularly for power constrained devices. A mobile sink based data transmission scheme can be one solution but obstacles create significant complexities for the sink movement path determination process. Therefore, an obstacle avoidance data routing scheme is of vital importance to the design of an efficient home automation system. This paper presents a mobile sink based obstacle avoidance routing scheme for a home monitoring system. The mobile sink collects data by traversing through the obstacle avoidance path. Through ZigBee based hardware implementation and verification, the proposed scheme successfully transmits data through the obstacle avoidance path to improve network performance in terms of life span, energy consumption and reliability. The application of this work can be applied to a wide range of intelligent pervasive consumer products and services including robotic vacuum cleaners and personal security robots1.

The EU societal awareness of landscape indicator: a review of its meaning, utility and performance across different scales

There is increasing recognition that agricultural landscapes meet multiple societal needs and demands beyond provision of economic and environmental goods and services. Accordingly, there have been significant calls for the inclusion of societal, amenity and cultural values in agri-environmental landscape indicators to assist policy makers in monitoring the wider impacts of land-based policies. However, capturing the amenity and cultural values that rural agrarian areas provide, by use of such indicators, presents significant challenges. The EU social awareness of landscape indicator represents a new class of generalized social indicator using a top-down methodology to capture the social dimensions of landscape without reference to the specific structural and cultural characteristics of individual landscapes. This paper reviews this indicator in the context of existing agri-environmental indicators and their differing design concepts. Using a stakeholder consultation approach in five case study regions, the potential and limitations of the indicator are evaluated, with a particular focus on its perceived meaning, utility and performance in the context of different user groups and at different geographical scales. This analysis supplements previous EU-wide assessments, through regional scale assessment of the limitations and potentialities of the indicator and the need for further data collection. The evaluation finds that the perceived meaning of the indicator does not vary with scale, but in common with all mapped indicators, the usefulness of the indicator, to different user groups, does change with scale of presentation. This indicator is viewed as most useful when presented at the scale of governance at which end users operate. The relevance of the different sub-components of the indicator are also found to vary across regions.

Review of monitoring tools for e-learning platforms

The advancement of e-learning technologies has made it viable for developments in education and technology to be combined in order to fulfil educational needs worldwide. E-learning consists of informal learning approaches and emerging technologies to support the delivery of learning skills, materials, collaboration and knowledge sharing. E-learning is a holistic approach that covers a wide range of courses, technologies and infrastructures to provide an effective learning environment. The Learning Management System (LMS) is the core of the entire e-learning process along with technology, content, and services. This paper investigates the role of model-driven personalisation support modalities in providing enhanced levels of learning and trusted assimilation in an e-learning delivery context. We present an analysis of the impact of an integrated learning path that an e-learning system may employ to track activities and evaluate the performance of learners.