Ayooluwaposi Olomo
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Ayooluwaposi Olomo has a total of 10 co-authors. Here are the top co-authors by number of shared publications:
- Andrew K. Chesang
Department of Biosystems and Agricultural Engineering, Michigan State University, East Lansing, MI 48823, USA
1 shared publication - Azlan Zahid
Department of Biological and Agricultural Engineering, TX A&M AgriLife Research Texas A&M University System Dallas Texas USA
1 shared publication - Daniel Dooyum Uyeh
Department of Biosystems and Agricultural Engineering, Michigan State University, East Lansing, MI 48824, USA
1 shared publication - John Temitope Ajayi
Department of Biosystems and Agricultural Engineering, Michigan State University, East Lansing, MI 48824, USA
1 shared publication - Judith Nkechinyere Njoku
Department of Biosystems and Agricultural Engineering, Michigan State University, East Lansing, MI 48824, USA
1 shared publication - Oluwaseun Opadotun
Department of Biosystems and Agricultural Engineering, Michigan State University, East Lansing, MI 48824, USA
1 shared publication
Latest Publications
- Open Access
- 23 September 2025
- Published by MDPI AG in Agriengineering
- Vol. 7 (10) , 315
A Digital Twin Framework for Sensor Selection and Microclimate Monitoring in Greenhouses
Digital twins, defined as virtual counterparts of physical systems that evolve with sensor data have potential applications in controlled-environment agriculture. This study previews the integration of adaptive Microclimate Monitoring within a Unity-based digital twin of a strawberry greenhouse to support dynamic sensor selection and reallocation. Using data collected from 56 distributed temperature–relative humidity sensors, a Thompson Sampling algorithm was deployed to assign monthly importance rankings and identify season-specific subsets of sensors. To evaluate how well these subsets represented the whole sensor network, we used the Z-index, which measures distributional consistency. Across all observed months, Z-index values remained close to zero, with values of 0.037 in February, 0.012 in April, −0.002 in June, and 0.025 in October for relative humidity. These results indicate that the digital twin framework sustains the overall climate trend while reducing sensing redundancy, pointing to its potential role in future climate monitoring strategies within greenhouse systems.
- 23 September 2025
- Published by MDPI AG in Agriengineering
- Vol. 7 (10) , 315
Open AccessA Digital Twin Framework for Sensor Selection and Microclimate Monitoring in Greenhouses
Digital twins, defined as virtual counterparts of physical systems that evolve with sensor data have potential applications in controlled-environment agriculture. This study previews the integration of adaptive Microclimate Monitoring within a Unity-based digital twin of a strawberry greenhouse to support dynamic sensor selection and reallocation. Using data collected from 56 distributed temperature–relative humidity sensors, a Thompson Sampling algorithm was deployed to assign monthly importance rankings and identify season-specific subsets of sensors. To evaluate how well these subsets represented the whole sensor network, we used the Z-index, which measures distributional consistency. Across all observed months, Z-index values remained close to zero, with values of 0.037 in February, 0.012 in April, −0.002 in June, and 0.025 in October for relative humidity. These results indicate that the digital twin framework sustains the overall climate trend while reducing sensing redundancy, pointing to its potential role in future climate monitoring strategies within greenhouse systems.