A steady increase in parcel volume has put more pressure on the freight transportation industry and will only continue to do so in the future. The whole industry will continue to grow as the volume increases which in turn will put more pressure on the drivers responsible that the goods arrive safely to their destination. There are many reasons to try and facilitate their working environment. It is very common for delivery drivers nowadays to use different mapping services to help navigate. The maps have helped a lot since their arrival, but this does not mean that they are faultless, there is still room for improvement. This study examines how mapping services can be used and updated to help drivers save time while deliveries. It focuses on public, free-to-use maps. A survey was conducted where drivers in the industry were asked questions about their use of mapping services and where they got to give their opinion on possible improvements to these. Motivated by observations in the field and the literature, the survey presented two potential improvements to the maps to gather opinions from the drivers. The first one was a possible addition of loading zones and loading docks to the mapping services in order to help drivers find their destination’s drop-off area. Previous studies have shown that drivers lose time in the last mile of their trip. The second problem occurs when a map navigates so that you approach your destination from the wrong direction. The study showed that delivery drivers today use maps very frequently. All 33 respondents in the study use a mapping service for their work at least once a week, 29 of them using one at least once a day. The drivers were very positive about a possible addition of loading zones and docks to the maps, all of them thought it would facilitate their work. After analysing the data collected it could be seen that an average driver loses 20 minutes a day searching for a place to load. The drivers were overall frustrated with the maps despite using them very frequently. They agreed with the problems presented in the survey and gave further examples of how they are being held back by the maps.

With the increase in applications of wireless sensor networks, data extraction and visualisation have become a key issue to develop and operate these networks. Wireless sensor networks typically gather data at a discrete number of locations. By bestowing the ability to predict inter-node values upon the network, it is proposed that it will become possible to build applications that are unaware of the concrete reality of sparse data. The aim of this thesis is to develop a service for maximising information return from large scale wireless sensor networks. This aim will be achieved through the development of a distributed information extraction and visualisation service called the mapping service. In the distributed mapping service, groups of network nodes cooperate to produce local maps which are cached and merged at a sink node, producing a map of the global network. Such a service would greatly simplify the production of higher-level information-rich representations suitable for informing other network services and the delivery of field information visualisations. The proposed distributed mapping service utilises a blend of both inductive and deductive models to successfully map sense data and the universal physical principles. It utilises the special characteristics of the application domain to render visualisations in a map format that are a precise reflection of the concrete reality. This service is suitable for visualising an arbitrary number of sense modalities. It is capable of visualising from multiple independent types of the sense data to overcome the limitations of generating visualisations from a single type of a sense modality. Furthermore, the proposed mapping service responds to changes in the environmental conditions that may impact the visualisation performance by continuously updating the application domain model in a distributed manner. Finally, a newdistributed self-adaptation algorithm, Virtual Congress Algorithm,which is based on the concept of virtual congress is proposed, with the goal of saving more power and generating more accurate data visualisation.