Abstract
For large-scale outdoor and indoor operations, improvement of work task logistics is an important focus area. Efficient handling of work task logistics is especially crucial for operations involving spatially distributed work tasks, such as hospital service logistics, large-scale manufacturing plants, or airports. For spatially distributed tasks, delays in a single task may propagate to multiple other tasks, causing large amounts of wasted time.
The planning and delegation of work tasks has traditionally been performed manually, using historical information on task execution combined with the intuition and personal experience of the planners.
Lack of real-time information on task execution has made it difficult to adapt to changes in the schedules, such as delays or suddenly occurring urgent tasks.
The recent advances in methods and devices for mobile sensing provides opportunities for developing methods for improving large-scale work task logistics. While research exists on using, e.g., GPS for improving outdoor logistics, research has been lacking for indoor settings. The research goal of this thesis is to take advantage of the opportunities provided by mobile sensing, by developing methods for spatio-temporal analysis of human activities in indoor environments based on mobile sensing. The methods aim to improve scheduling and facility utilization by providing information on the used route networks, transportation modes, travel times, and the flow of people through buildings. The methods are based on large-scale real-time indoor positioning through the use of existing WiFi infrastructures, which allows for easy deployment even in very large building complexes. The methods are designed for real-time operation, which enables them to detect and adjust to changes as they occur.
The methods are developed in the settings of the PosLogistics project, in collaboration with a software company and two Danish hospitals, and evaluated using data collected at the hospitals. Evaluations show that the methods are able to accurately reconstruct route networks, provide common route and travel time estimates, detect transportation modes, and provide information for facility utilization. Although the focus of the evaluations are on hospital settings, we argue that the methods are generalizable to other large-scale indoor logistics operations, such as airports or warehouses.
The planning and delegation of work tasks has traditionally been performed manually, using historical information on task execution combined with the intuition and personal experience of the planners.
Lack of real-time information on task execution has made it difficult to adapt to changes in the schedules, such as delays or suddenly occurring urgent tasks.
The recent advances in methods and devices for mobile sensing provides opportunities for developing methods for improving large-scale work task logistics. While research exists on using, e.g., GPS for improving outdoor logistics, research has been lacking for indoor settings. The research goal of this thesis is to take advantage of the opportunities provided by mobile sensing, by developing methods for spatio-temporal analysis of human activities in indoor environments based on mobile sensing. The methods aim to improve scheduling and facility utilization by providing information on the used route networks, transportation modes, travel times, and the flow of people through buildings. The methods are based on large-scale real-time indoor positioning through the use of existing WiFi infrastructures, which allows for easy deployment even in very large building complexes. The methods are designed for real-time operation, which enables them to detect and adjust to changes as they occur.
The methods are developed in the settings of the PosLogistics project, in collaboration with a software company and two Danish hospitals, and evaluated using data collected at the hospitals. Evaluations show that the methods are able to accurately reconstruct route networks, provide common route and travel time estimates, detect transportation modes, and provide information for facility utilization. Although the focus of the evaluations are on hospital settings, we argue that the methods are generalizable to other large-scale indoor logistics operations, such as airports or warehouses.
| Original language | English |
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| Publisher | |
| Publication status | Published - 30 Sept 2015 |