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Daniel Queirós Silva
Daniel Queirós da Silva was born in Ermesinde, Porto, Portugal, in 1997. He obtained the M.Sc. degree in Electrical and Computer Engineering from the Faculty of Engineering of the University of Porto (FEUP) in 2020, and the Ph.D. degree in Electrical and Computer Engineering from the University of Trás-os-Montes and Alto Douro (UTAD) in 2024. He is currently a Researcher at INESC Technology and Science (INESC TEC) and an Invited Assistant Lecturer at the School of Engineering of the Polytechnic of Porto (ISEP). His main research interests are perception systems, artificial intelligence, robotics and embedded systems.
Projects
PRySM
Steep slope vineyards account for 10% - 12% of European viticulture land area and produce some of the highest value wines. Row sizes are quite narrow, typically 90 – 150cm. Currently, where possible, treatments are applied from a small tractor-based system that considers an air-blast based system. Losses are high and ground compaction is a problem. Inspired by this problem, this project develops a modular and precision terrestrial sprayer robot – the Precision Robotic Sprayer (PRySM) - capable of operating autonomously on rugged terrain with steep slopes and under the most diverse ground conditions. A robotic platform will be adapted to work on hard terrain conditions and whose dimensions and locomotion mechanism allow tight manoeuvring in the context of mountain vineyards with very narrow rows. To this robot will be added advanced algorithms for self-localization and navigating using LiDAR and GNSS receiver data to support precision spraying tasks. The project will develop and integrate a novel precision autonomous spray tool into the developed robotic platform. The PRYSM robot will be tested and validated in a steep slope vineyard and perform an autonomous precision spraying operation during the first demonstration. This project has received funding from the ESMERA EU Funded project which belongs to the European Union’s Horizon 2020 research and innovation programme under grant agreement No 780265 Pulverizadores Rocha
Replant
At a time when the forest and forest sector are on the agenda, and discussing ways to increase the sector's competitiveness alongside the country's socio-economic development in the context of a global circular economy, this mobilizing project comes bring a new perspective on integrated forest and fire management, based on scientific and technological knowledge. The main purpose of this mobilizer is to contribute to the greater appreciation of the Portuguese forest through the implementation of collaborative strategies for integrated forest and fire management. These strategies will lead to new products and services, mostly supported by digital technologies, contributing to fire risk reduction and introducing a high degree of innovation to improve forest and energy companies' management and decision-making processes, with positive impacts throughout the chain, including its service providers and forest producers, with a major impact on the economy of rural areas. RePLANt will contribute to consolidate the national market in technologies and equipment for the forest sector. RePLANt is the first major project that will enable the ForestWISE Collaborative Laboratory to be operationalized. This is an unprecedented effort to take the priority business initiatives outlined in the ForestWISE R&D Agenda to the ground. The project brings together all ForestWISE associates - forestry, energy companies and universities - which together represent all the diversity of the national forestry sector, working together with hi-tech companies. This multidisciplinary consortium will implement major 8 Collaborative Strategies, structured in industrial research activities of 3 major PPS3 - Forest and fire management, risk management and circular economy and value chains. Project datasheet
Publications
YOLO-Based Tree Trunk Types Multispectral Perception: A Two-Genus Study at Stand-Level for Forestry Inventory Management Purposes
da Silva, DQ;Dos Santos, FN;Filipe, V;Sousa, AJ;Pires, EJS;
2024
IEEE ACCESS
Assessing Soil Ripping Depth for Precision Forestry with a Cost-Effective Contactless Sensing System
da Silva, DQ;Louro, F;dos Santos, FN;Filipe, V;de Sousa, AJM;Cunha, M;Carvalho, JL;
2023
Robot 2023: Sixth Iberian Robotics Conference - Advances in Robotics, Volume 2, Coimbra, Portugal, 22-24 November 2023.
Deep Learning-Based Tree Stem Segmentation for Robotic Eucalyptus Selective Thinning Operations
da Silva, DQ;Rodrigues, TF;Sousa, AJ;dos Santos, FN;Filipe, V;
2023
PROGRESS IN ARTIFICIAL INTELLIGENCE, EPIA 2023, PT II
Deep Learning YOLO-Based Solution for Grape Bunch Detection and Assessment of Biophysical Lesions
Pinheiro, I;Moreira, G;da Silva, DQ;Magalhaes, S;Valente, A;Oliveira, PM;Cunha, M;Santos, F;
2023
AGRONOMY-BASEL
