Task phase recognition for highly mobile workers in large building complexes

Abstract

Being aware of activities of co-workers is a basic and vital mechanism for efficient work in highly distributed work settings. Thus, automatic recognition of the task phases the mobile workers are currently (or have been) in has many applications, e.g., efficient coordination of tasks by visualizing coworkers' task progress, automatic notifications based on context awareness, and record filing of task statuses and completions.This paper presents methods to sense and detect highly mobile workers' tasks phases in large building complexes. Large building complexes restrict the technologies available for sensing and recognizing the activities and task phases the workers currently perform as such technologies have to be easily deployable and maintainable at a large scale. The methods presented in this paper consist of features that utilize data from sensing systems which are common in large-scale indoor work environments, namely from a WiFi infrastructure providing coarse grained indoor positioning, from inertial sensors in the workers' mobile phones, and from a task management system yielding information about the scheduled tasks' start and end locations. The methods presented have low requirements on the accuracy of the indoor positioning, and thus come with low deployment and maintenance effort in real-world settings.We evaluated the proposed methods in a large hospital complex, where the highly mobile workers were recruited among the non-clinical workforce. The evaluation is based on manually labelled real-world data collected over 4 days of regular work life of the mobile workforce. The collected data yields 83 tasks in total involving 8 different orderlies from a major university hospital with a building area of 160, 000 m 2 . The results show that the proposed methods can distinguish accurately between the four most common task phases present in the orderlies' work routines, achieving F1-Scores of 89.2%.

Indoor positioning systems in hospitals: A scoping review

“…The reasons therefore are various, for example, to adapt the IPS to meet certain demands of specific stakeholder groups 44 or to meet the overall aim of the IPS. 4,55 Unfortunately, reports about (iv) energy efficiency are disputed as well, as they are often not available, despite the fact that (iv) energy efficiency is important for IPS, since some studies addressed this aspect accurately (e.g. Refs.…”

“…The use of those innovations in hospitals is of special importance, especially under consideration of pandemic crises and needs for isolation. 2,3 Because health measures are highly complex and handled individually, 4 it is important to use the already scarce resources efficiently and to avoid redundant activities. 4–6 Indoor Positioning Systems (IPS) as measures to track people and objects 7 should help to ensure that no resources for redundant activities in this context are raised, for example, finding the right room or important objects, such as respirators.…”

Recognition of Group Mobility Level and Group Structure with Mobile Devices

“…Research on group behavior recognition covers many scenarios in reality [26], [32], [33], [34]. Sebastian et al [26] utilized smartphones and detected group proximity dynamics of firefighting teams.…”

“…Based on sensor signals and social signal processing, Eyal et al [32] detected typical social behavior patterns of visitor pairs, knowing the social context. Utilizing deployed Wi-Fi infrastructures and accelerometer from smartphones, Allan et al [34] recognized task phase for mobile workers in large buildings, such as in a hospital. Applications used in these works may be built on our framework.…”

An Automated Recognition of Work Activity in Industrial Manufacturing Using Convolutional Neural Networks

“…The factory workers' assembly labor is still at the heart of the industrial manufacturing system, and improving assembly work is one of the most critical tasks for increasing productivity [4]. The awareness of worker activities in spatially-extant and distributed manufacturing facilities is a pre-requisite for efficient workflow organization [5]. For example, a worker in a conveyor line-based production system conducts predetermined operation procedures repeatedly, each of which consists of a sequence of operations.…”