simulated smart house; 2) there is no unspecified time in the timeline of generated
schedules; and 3) it generates stable, but not tedious schedules for a number of days.
A generated schedule includes a list of activities and their start time. The list of
activities determines all starts and ends of indoor walking paths with spatial attributes
of a virtual house, the travel pattern generator then generates all paths. The generated
paths determine simulated real-time locations of a resident with the list of start time.
The real-time locations can be converted to records of virtual sensors with interfaces, and these records can be used to optimize designs of smart house. For example,
we convert the real-time locations to records of virtual PIR sensors, and the records are
useful for optimizing placement of these sensors.
Acknowledgments. This research was partially supported by a grant from the Japan Society for
the Promotion of Science (JSPS KAKENHI 18H00968) and a scholarship of Mizuho International Foundation.
References
1. He, W., Goodkind, D., Smith, P.K.: An Aging World: 2015: International Population
Reports, U.S. Census Bureau (2016)
2. Reher, D., Requena, M.: Living alone in later life: a global perspective. Popul. Dev. Rev.
44(3), 427–454 (2018)
3. Pimouguet, C., et al.: Impact of living alone on institutionalization and mortality: a
population-based longitudinal study. Eur. J. Public Health 26(1), 182–187 (2016)
4. Simoens, S., Villeneuve, M., Hurst, J.: Tackling nurse shortages in OECD countries:
Technology Report, Organisation for Economic Co-operation and Development (2005)
5. Vuong, N.K., Chan, S., Lau, C.T., Chan, S.Y., Yap, P.L., Chen, A.S.: Preliminary results of
using inertial sensors to detect dementia-related wandering patterns. In: Proceedings of 37th
International Conference on Engineering in Medicine and Biology Society (EMBC2015),
Milan, pp. 3703–3706 (2015)
6. Das, B., Cook, D.J., Krishnan, N.C., Schmitter-Edgecombe, M.: One-class classificationbased real-time activity error detection in smart homes. IEEE. JSTSP 10(5), 914–923 (2016)
7. Do, H.M., Pham, M., Sheng, W., Yang, D., Liu, M.: RiSH: a robot-integrated smart home
for elderly care. Rob. Auton. Syst. 101, 74–92 (2018)
8. Fischinger, D., et al.: Hobbit, a care robot supporting independent living at home: first
prototype and lessons learned. Rob. Auton. Syst. 75(A), 60–78 (2016)
9. Alshammari, N., Alshammari, T., Sedky, M., Champion, J., Bauer, C.: OpenSHS: open
smart home simulator. Sensors 17, 1003 (2017)
10. Vaughan, R.: Massively multi-robot simulation in stage. Swarm Intell. 2, 189–208 (2008)
11. Jiang, C., Mita, A.: Automatic spatial attribute and travel pattern generation for simulating
living spaces for elderly individuals living alone. Build. Environ. 176, 106776 (2020).
https://doi.org/10.1016/j.buildenv.2020.106776
12. Jiang, C., Mita, A.: Automatic floorplan generation of living space for simulating a life of an
elderly resident supported by a mobile robot. In: Proceedings of 36th International
Symposium on Automation and Robotics in Construction (ISARC 2019), Banff, pp. 688–
695 (2019)
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schedules; and 3) it generates stable, but not tedious schedules for a number of days.
A generated schedule includes a list of activities and their start time. The list of
activities determines all starts and ends of indoor walking paths with spatial attributes
of a virtual house, the travel pattern generator then generates all paths. The generated
paths determine simulated real-time locations of a resident with the list of start time.
The real-time locations can be converted to records of virtual sensors with interfaces, and these records can be used to optimize designs of smart house. For example,
we convert the real-time locations to records of virtual PIR sensors, and the records are
useful for optimizing placement of these sensors.
Acknowledgments. This research was partially supported by a grant from the Japan Society for
the Promotion of Science (JSPS KAKENHI 18H00968) and a scholarship of Mizuho International Foundation.
References
1. He, W., Goodkind, D., Smith, P.K.: An Aging World: 2015: International Population
Reports, U.S. Census Bureau (2016)
2. Reher, D., Requena, M.: Living alone in later life: a global perspective. Popul. Dev. Rev.
44(3), 427–454 (2018)
3. Pimouguet, C., et al.: Impact of living alone on institutionalization and mortality: a
population-based longitudinal study. Eur. J. Public Health 26(1), 182–187 (2016)
4. Simoens, S., Villeneuve, M., Hurst, J.: Tackling nurse shortages in OECD countries:
Technology Report, Organisation for Economic Co-operation and Development (2005)
5. Vuong, N.K., Chan, S., Lau, C.T., Chan, S.Y., Yap, P.L., Chen, A.S.: Preliminary results of
using inertial sensors to detect dementia-related wandering patterns. In: Proceedings of 37th
International Conference on Engineering in Medicine and Biology Society (EMBC2015),
Milan, pp. 3703–3706 (2015)
6. Das, B., Cook, D.J., Krishnan, N.C., Schmitter-Edgecombe, M.: One-class classificationbased real-time activity error detection in smart homes. IEEE. JSTSP 10(5), 914–923 (2016)
7. Do, H.M., Pham, M., Sheng, W., Yang, D., Liu, M.: RiSH: a robot-integrated smart home
for elderly care. Rob. Auton. Syst. 101, 74–92 (2018)
8. Fischinger, D., et al.: Hobbit, a care robot supporting independent living at home: first
prototype and lessons learned. Rob. Auton. Syst. 75(A), 60–78 (2016)
9. Alshammari, N., Alshammari, T., Sedky, M., Champion, J., Bauer, C.: OpenSHS: open
smart home simulator. Sensors 17, 1003 (2017)
10. Vaughan, R.: Massively multi-robot simulation in stage. Swarm Intell. 2, 189–208 (2008)
11. Jiang, C., Mita, A.: Automatic spatial attribute and travel pattern generation for simulating
living spaces for elderly individuals living alone. Build. Environ. 176, 106776 (2020).
https://doi.org/10.1016/j.buildenv.2020.106776
12. Jiang, C., Mita, A.: Automatic floorplan generation of living space for simulating a life of an
elderly resident supported by a mobile robot. In: Proceedings of 36th International
Symposium on Automation and Robotics in Construction (ISARC 2019), Banff, pp. 688–
695 (2019)
182
C. Jiang and A. Mita