The construction and logistics sectors in the Netherlands are rapidly increasing in size, but unfortunately are also part of the most hazardous industries. One part of safety which needs to be addressed is manual handling related incidents. The moving of objects around a worksite
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The construction and logistics sectors in the Netherlands are rapidly increasing in size, but unfortunately are also part of the most hazardous industries. One part of safety which needs to be addressed is manual handling related incidents. The moving of objects around a worksite through utilization of an employee’s body increases the exposure of the employees to hazards, especially if done incorrectly, and will increase costs for both employee and employer. This thesis explores the possibility of transforming the passive and reactive role of safety shoes into safety shoes that are capable of proactive (manual handling related) incident prevention, through utilization of smart technology. To gain insight into the problem, its context and the possibilities for the implementation of smart technology, an extensive literature review was conducted. In addition, practical field knowledge was gained through multiple series of semi-structured interviews and analysis of relevant cases. Research results show that the human factor plays a major role in the causation of occupational incidents and can be divided into three categories: the individual, the task and the organisation. As this human factor is either the leading cause or part of the cause for around 80% of all incidents, it is vital for incident prevention. Furthermore, current methods for detection and prevention (e.g. manual handling training and safety programs) have serious shortcomings which make them less effective tools for the reduction or elimination of manual handling related incidents. In addition to this, studies indicate the opportunity for (smart) technology to aid in overcoming these shortcomings. The above mentioned insights served as input for the synthesis of a concept design (smart safety shoes), which uses sensors and data analysis tools (e.g. machine learning) to identify and detect leading and lagging indicators for manual handling related incidents and subsequently is able to effectively communicate those insights to different parties: employees, employers, supervisors and training providers. The smart safety shoes can, in this manner, support current detection and prevention methods in their shortcomings. The before mentioned parties deploy the insights through a hybrid system: reactive incident prevention (improve the individual) and proactive prevention (improve task design and organization), which both, increase incident prevention. The concept design is accompanied by a roadmap outlining the general steps for the development of the concept. To conclude, smart safety shoes are the next step towards occupational incident prevention and potentially the first step towards smart, ubiquitous, occupational safety. However, further research is needed for the development of the smart safety shoes and the exploration of further possibilities. In addition to this, the principles behind the smart safety shoes could serve as a basis for further design research, to address other occupational safety issues and other industries.