Device-Free, Activity during Daily Life, Recognition Using a Low-Cost Lidar

Device-free or off-body sensing methods, such as Lidar, can be used for location-driven Activities during Daily Life (ADL) recognition without the need for a mobile host such as a human or robot to use on-body location sensors. Because if such an attachment fails, or is not operational (powered up), when such mobile hosts are device free, it still works. Hence, this paper proposes an innovative method for recognizing ADLs using a state-of-art seq2seq Recurrent Neural Network (RNN) model to classify centimeter level accurate location data from a low-cost, 360°rotating 2D Lidar device. We researched, developed, deployed and validated the system. The results indicate that it can provide a centimeter-level localization accuracy of 88% when recognizing 17 targeted location-related daily activities

Estudo do efeito ambiental sobre o comportamento meiótico de variedades de trigo.

bitstream/item/116676/1/FOL-00111.pdfTrabalho apresentado na IX Reunião Anual Conjunta de Pesquisa de Trigo, Londrina, 1977. Mimeografado

Device-Free Daily Life (ADL) Recognition for Smart Home Healthcare using a low-cost (2D) Lidar

Device-free or off-body sensing methods such as Lidar can be used for location-related Activities during Daily Life (ADL) recognition without the need for the subject to carry less accurate on-body sensors and because some subjects may forget to carry them or maintain them to be operational (powered up), i.e., users can be device free and the method still works. Hence, this paper proposes an innovative method for recognizing daily activities using a state-of-art seq2seq Recurrent Neural Network (RNN) model to classify centimeter level accurate location data from a 360-degree rotating 2D Lidar device. We deployed and validated the system. The results indicate that our method can provide a centimeter-level localization accuracy of 88% when recognizing seventeen targeted location-related daily activities

Estudo do comportamento meiótico e formação do pólen na cultivar de trigo C15, submetida à ação de defensivos.

bitstream/item/116672/1/FOL-00110.pdfTrabalho apresentado na IX Reunião Anual Conjunta de Pesquisa de Trigo, Londrina, 1977. Mimeografado

Device-Free Daily Life (ADL) Recognition for Smart Home Healthcare using a low-cost (2D) Lidar

Device-free or off-body sensing methods such as Lidar can be used for location-related Activities during Daily Life (ADL) recognition without the need for the subject to carry less accurate on-body sensors and because some subjects may forget to carry them or maintain them to be operational (powered up), i.e., users can be device free and the method still works. Hence, this paper proposes an innovative method for recognizing daily activities using a state-of-art seq2seq Recurrent Neural Network (RNN) model to classify centimeter level accurate location data from a 360-degree rotating 2D Lidar device. We deployed and validated the system. The results indicate that our method can provide a centimeter-level localization accuracy of 88% when recognizing seventeen targeted location-related daily activities