| INDÚSTRIA 4.0: DESAFIOS E OPORTUNIDADES BP Santos, A Alberto, TDFM Lima, FMB Charrua-Santos Revista Produção e Desenvolvimento 4 (1), 111-124, 2018 | 251* | 2018 |
| Industry 4.0 and Society 5.0: opportunities and threats AG Pereira, TM Lima, FC Santos International Journal of Recent Technology and Engineering 8 (5), 3305-3308, 2020 | 225 | 2020 |
| Is industry 5.0 a human-centred approach? a systematic review J Alves, TM Lima, PD Gaspar Processes 11 (1), 193, 2023 | 89 | 2023 |
| Crop yield estimation using deep learning based on climate big data and irrigation scheduling K Alibabaei, PD Gaspar, TM Lima Energies 14 (11), 3004, 2021 | 68 | 2021 |
| Industry 4.0: An Overwiew BP Santos, F Charrua-Santos, TM Lima ICMEEM 2018 - International Conference of Manufacturing Engineering and …, 2018 | 67* | 2018 |
| Advantages and difficulties of implementing Industry 4.0 technologies for labor flexibility DV Enrique, JCM Druczkoski, TM Lima, F Charrua-Santos Procedia Computer Science 181, 347-352, 2021 | 48 | 2021 |
| Ergonomic and psychosocial factors and musculoskeletal complaints in public sector administration–a joint monitoring approach with analysis of association TM Lima, DA Coelho International journal of industrial ergonomics 66, 85-94, 2018 | 43 | 2018 |
| A review of the challenges of using deep learning algorithms to support decision-making in agricultural activities K Alibabaei, PD Gaspar, TM Lima, RM Campos, I Girão, J Monteiro, ... Remote Sensing 14 (3), 638, 2022 | 42 | 2022 |
| What is the role of active packaging in the future of food sustainability? A systematic review J Alves, PD Gaspar, TM Lima, PD Silva Journal of the Science of Food and Agriculture 103 (3), 1004-1020, 2023 | 37 | 2023 |
| Artificial intelligence for product quality inspection toward smart industries: quality control of vehicle non-conformities A Chouchene, A Carvalho, TM Lima, F Charrua-Santos, GJ Osório, ... 2020 9th international conference on industrial technology and management …, 2020 | 37 | 2020 |
| Irrigation optimization with a deep reinforcement learning model: Case study on a site in Portugal K Alibabaei, PD Gaspar, E Assunção, S Alirezazadeh, TM Lima Agricultural Water Management 263, 107480, 2022 | 35 | 2022 |
| Modeling soil water content and reference evapotranspiration from climate data using deep learning method K Alibabaei, PD Gaspar, TM Lima Applied Sciences 11 (11), 5029, 2021 | 34 | 2021 |
| Cognitive manufacturing in industry 4.0 toward cognitive load reduction: A conceptual framework AV Carvalho, A Chouchene, TM Lima, F Charrua-Santos Applied System Innovation 3 (4), 55, 2020 | 34 | 2020 |
| Prevention of musculoskeletal disorders (MSDs) in office work: A case study TM Lima, DA Coelho Work 39 (4), 397-408, 2011 | 32 | 2011 |
| Society 5.0 as a result of the technological evolution: Historical approach AG Pereira, TM Lima, F Charrua-Santos Human Interaction and Emerging Technologies: Proceedings of the 1st …, 2020 | 31 | 2020 |
| Innovative processes in smart packaging. A systematic review CM Fernandez, J Alves, PD Gaspar, TM Lima, PD Silva Journal of the Science of Food and Agriculture 103 (3), 986-1003, 2023 | 30 | 2023 |
| Fostering awareness on environmentally sustainable technological solutions for the post-harvest food supply chain CM Fernandez, J Alves, PD Gaspar, TM Lima Processes 9 (9), 1611, 2021 | 27 | 2021 |
| Environmental risk assessment and management in industry 4.0: a review of technologies and trends J Lemos, PD Gaspar, TM Lima Machines 10 (8), 702, 2022 | 26 | 2022 |
| Working conditions under multiple exposures: A cross-sectional study of private sector administrative workers DA Coelho, CSD Tavares, ML Lourenço, TM Lima Work 51 (4), 781-789, 2015 | 26 | 2015 |
| The synergic relationship between industry 4.0 and lean management: Best practices from the literature BP Santos, DV Enrique, VBP Maciel, TM Lima, F Charrua-Santos, ... Management and Production Engineering Review 12 (1), 94-107, 2021 | 25 | 2021 |
Pedro Dinis GasparProfessor, University of Beira Interior在 ubi.pt 的电子邮件经过验证
