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About

About

Emanuel Soares Peres Correia is an assistant professor at Trás-os-Montes e Alto Douro University (UTAD) in Portugal. He has been lecturing in areas such as web development, electronics, power electronics, telecommunications and computer networks since 2003. He is an integrated researcher at the Centre for Robotics in Industry and Intelligent Systems (CRIIS) in Technology and Science Associate Laboratory (INESC-TEC) and his research focuses on combining sensing networks, in-field processing units and mesh communication networks to develop data acquisition systems which enable decision support tools for precision agriculture. Human–Machine interaction, namely augmented reality systems and new interfaces, in areas such as education, agriculture and tourism, is also an area of interest. His research has been presented at international conferences such as CENTERIS, EDUCON, CISTI, CSEDU and SPIE and he has been published in the e.g. Journal of Computers and Electronics in Agriculture, Journal of Remote Sensing, International Journal of Remote Sensing, Journal of Theoretical and Applied Electronic Commerce Research, Journal of Applied Logic and Procedia Technology. He is an Editor-in-Chief of the International Journal of Web Portals (IJWP) since November 2016. As a member of UTAD’s Urban Eco-Efficiency Unit, he is currently involved in several research projects mainly related with the application of UAV in agriculture and forestry.

Interest
Topics
Details

Details

001
Publications

2021

Preface

Authors
Cruz Cunha, MM; Martinho, R; Rijo, R; Peres, E; Domingos, D; Mateus Coelho, N;

Publication
Procedia Computer Science

Abstract

2021

A Versatile, Low-Power and Low-Cost IoT Device for Field Data Gathering in Precision Agriculture Practices

Authors
Morais, R; Mendes, J; Silva, R; Silva, N; Sousa, JJ; Peres, E;

Publication
Agriculture

Abstract
Spatial and temporal variability characterization in Precision Agriculture (PA) practices is often accomplished by proximity data gathering devices, which acquire data from a wide variety of sensors installed within the vicinity of crops. Proximity data acquisition usually depends on a hardware solution to which some sensors can be coupled, managed by a software that may (or may not) store, process and send acquired data to a back-end using some communication protocol. The sheer number of both proprietary and open hardware solutions, together with the diversity and characteristics of available sensors, is enough to deem the task of designing a data acquisition device complex. Factoring in the harsh operational context, the multiple DIY solutions presented by an active online community, available in-field power approaches and the different communication protocols, each proximity monitoring solution can be regarded as singular. Data acquisition devices should be increasingly flexible, not only by supporting a large number of heterogeneous sensors, but also by being able to resort to different communication protocols, depending on both the operational and functional contexts in which they are deployed. Furthermore, these small and unattended devices need to be sufficiently robust and cost-effective to allow greater in-field measurement granularity 365 days/year. This paper presents a low-cost, flexible and robust data acquisition device that can be deployed in different operational contexts, as it also supports three different communication technologies: IEEE 802.15.4/ZigBee, LoRa/LoRaWAN and GRPS. Software and hardware features, suitable for using heat pulse methods to measure sap flow, leaf wetness sensors and others are embedded. Its power consumption is of only 83 µA during sleep mode and the cost of the basic unit was kept below the EUR 100 limit. In-field continuous evaluation over the past three years prove that the proposed solution—SPWAS’21—is not only reliable but also represents a robust and low-cost data acquisition device capable of gathering different parameters of interest in PA practices.

2020

Digital Reconstitution of Road Traffic Accidents: A Flexible Methodology Relying on UAV Surveying and Complementary Strategies to Support Multiple Scenarios

Authors
Padua, L; Sousa, J; Vanko, J; Hruska, J; Adao, T; Peres, E; Sousa, A; Sousa, JJ;

Publication
International Journal of Environmental Research and Public Health

Abstract
The reconstitution of road traffic accidents scenes is a contemporary and important issue, addressed both by private and public entities in different countries around the world. However, the task of collecting data on site is not generally focused on with the same orientation and relevance. Addressing this type of accident scenario requires a balance between two fundamental yet competing concerns: (1) information collecting, which is a thorough and lengthy process and (2) the need to allow traffic to flow again as quickly as possible. This technical note proposes a novel methodology that aims to support road traffic authorities/professionals in activities involving the collection of data/evidences of motor vehicle collision scenarios by exploring the potential of using low-cost, small-sized and light-weight unmanned aerial vehicles (UAV). A high number of experimental tests and evaluations were conducted in various working conditions and in cooperation with the Portuguese law enforcement authorities responsible for investigating road traffic accidents. The tests allowed for concluding that the proposed method gathers all the conditions to be adopted as a near future approach for reconstituting road traffic accidents and proved to be: faster, more rigorous and safer than the current manual methodologies used not only in Portugal but also in many countries worldwide.

2020

Forestry Remote Sensing from Unmanned Aerial Vehicles: A Review Focusing on the Data, Processing and Potentialities

Authors
Guimaraes, N; Padua, L; Marques, P; Silva, N; Peres, E; Sousa, JJ;

Publication
Remote Sensing

Abstract
Currently, climate change poses a global threat, which may compromise the sustainability of agriculture, forestry and other land surface systems. In a changing world scenario, the economic importance of Remote Sensing (RS) to monitor forests and agricultural resources is imperative to the development of agroforestry systems. Traditional RS technologies encompass satellite and manned aircraft platforms. These platforms are continuously improving in terms of spatial, spectral, and temporal resolutions. The high spatial and temporal resolutions, flexibility and lower operational costs make Unmanned Aerial Vehicles (UAVs) a good alternative to traditional RS platforms. In the management process of forests resources, UAVs are one of the most suitable options to consider, mainly due to: (1) low operational costs and high-intensity data collection; (2) its capacity to host a wide range of sensors that could be adapted to be task-oriented; (3) its ability to plan data acquisition campaigns, avoiding inadequate weather conditions and providing data availability on-demand; and (4) the possibility to be used in real-time operations. This review aims to present the most significant UAV applications in forestry, identifying the appropriate sensors to be used in each situation as well as the data processing techniques commonly implemented.

2020

Individual Grapevine Analysis in a Multi-Temporal Context Using UAV-Based Multi-Sensor Imagery

Authors
Padua, L; Adao, T; Sousa, A; Peres, E; Sousa, JJ;

Publication
Remote Sensing

Abstract
The use of unmanned aerial vehicles (UAVs) for remote sensing applications in precision viticulture significantly increased in the last years. UAVs’ capability to acquire high spatiotemporal resolution and georeferenced imagery from different sensors make them a powerful tool for a better understanding of vineyard spatial and multitemporal heterogeneity, allowing the estimation of parameters directly impacting plants’ health status. In this way, the decision support process in precision viticulture can be greatly improved. However, despite the proliferation of these innovative technologies in viticulture, most of the published studies rely only on data from a single sensor in order to achieve a specific goal and/or in a single/small period of the vineyard development. In order to address these limitations and fully exploit the advantages offered by the use of UAVs, this study explores the multi-temporal analysis of vineyard plots at a grapevine scale using different imagery sensors. Individual grapevine detection enables the estimation of biophysical and geometrical parameters, as well as missing grapevine plants. A validation procedure was carried out in six vineyard plots focusing on the detected number of grapevines and missing grapevines. A high overall agreement was obtained concerning the number of grapevines present in each row (99.8%), as well as in the individual grapevine identification (mean overall accuracy of 97.5%). Aerial surveys were conducted in two vineyard plots at different growth stages, being acquired for RGB, multispectral and thermal imagery. Moreover, the extracted individual grapevine parameters enabled us to assess the vineyard variability in a given epoch and to monitor its multi-temporal evolution. This type of analysis is critical for precision viticulture, constituting as a tool to significantly support the decision-making process.

Supervised
thesis

2020

Elearning implementation at small universities

Author
Carlos Manuel Rodrigues Soares Vaz

Institution
UTAD

2020

Hyperspectral data analysis for agriculture applications

Author
Jonas Hruska

Institution
UTAD

2020

Automatic analysis of UAS-based multi-temporal data as support to a precision agroforestry management system

Author
Luís Filipe Machado Pádua

Institution
UTAD

2020

Sistemas cognitivos de interpretação inteligente em contexto agro-florestal

Author
Miguel Moreira da Silva Lima Barbosa

Institution
UP-FCUP

2019

Automatic analysis of UAS-based multi-temporal data as support to a precision agroforestry management system

Author
Luís Filipe Machado Pádua

Institution
UTAD