Article
Agronomy
Ali Roshanianfard, Noboru Noguchi, Sina Ardabili, Csaba Mako, Amir Mosavi
Summary: This study focused on the development, optimization, and evaluation of a harvesting robot for heavyweight agricultural products to improve the harvesting process. Pumpkin was selected as the target crop, and the robot consisted of mobile platforms, a manipulation system, an end-effector, and a control unit. The performance of the robot was evaluated, showing good accuracy, repeatability, harvesting success rate, and low damage rate. The development of this unified system proved to be effective in harvesting big-sized and heavy-weighted crops, increasing speed and efficiency.
Article
Energy & Fuels
Junnan Zhao, Yuli Xiong, Hangfei Wu, Mufeng Xi, Hong Liu, Shuai Guo, Lin Yang, Swee Ching Tan
Summary: A self-sustainable atmospheric water irrigation system has been developed for plant growth in arid land, which utilizes a super hygroscopic hydrogel to capture and release water from the air. The hydrogel relies on physisorption to accumulate water and can release it under sunlight. This solar energy-driven water recycling system produces water that meets international drinking water standards and promotes rapid growth of plants.
Article
Chemistry, Analytical
Aristotelis C. Tagarakis, Evangelia Filippou, Damianos Kalaitzidis, Lefteris Benos, Patrizia Busato, Dionysis Bochtis
Summary: This study investigates the application of RGB-D cameras and unmanned ground vehicles for autonomously mapping agricultural environments. The results show that RGB-D cameras can accurately calculate tree volume and provide similar height measurements compared to orthomosaics acquired by unmanned aerial vehicles.
Review
Chemistry, Analytical
Yogeswaranathan Kalyani, Rem Collier
Summary: Cloud Computing has limitations in ultra-low latency, high bandwidth, security, and real-time analytics when dealing with large amounts of data, where Fog and Edge Computing offer solutions. The use of Cloud, Fog, and Edge in smart agriculture applications is increasing, with this article aiming to review current works in this area. The review identifies relevant research, proposes a new architecture model, and discusses components, communication protocols, challenges, and future research directions in smart agriculture.
Article
Computer Science, Artificial Intelligence
Jiaping Yu, Haiwen Chen, Kui Wu, Tongqing Zhou, Zhiping Cai, Fang Liu
Summary: Smart cameras are widely used for surveillance, but security concerns have become a focus. EviChain proposes a blockchain-based solution to protect intelligent surveillance cameras and reduce costs through a collaborative mechanism.
INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS
(2022)
Article
Computer Science, Hardware & Architecture
P. Habeeb, Nabarun Deka, Deepak D'Souza, Kamal Lodaya, Pavithra Prabhakar
Summary: This paper investigates the problem of verifying the safety of camera-based autonomous vehicle trajectories in a given 3-D scene and presents a verification procedure and prioritization-based falsification procedure. Experimental results demonstrate the feasibility and benefits of the approach based on image-invariant regions for safety analysis and falsification.
IEEE TRANSACTIONS ON COMPUTER-AIDED DESIGN OF INTEGRATED CIRCUITS AND SYSTEMS
(2023)
Article
Energy & Fuels
Xiang Li, Yuying Cao, Xin Yu, Yuhong Xu, Yanfei Yang, Shiming Liu, Tinghai Cheng, Zhong Lin Wang
Summary: With the utilization of lightweight rotor materials and suitable wind scoop structures, the breeze-driven triboelectric nano generator can efficiently harvest energy even at low wind speeds, making it ideal for agricultural sensor networks in farmland environments.
Article
Computer Science, Information Systems
Ayalew Kassahun, Robbin Bloo, Cagatay Catal, Alok Mishra
Summary: The study conducted a comprehensive review of 50 FMIS used in the Dutch dairy sector, identifying 33 features and listing the advantages and disadvantages of these systems.
Article
Robotics
Hesheng Yin, Qixin Sun, Xu Ren, Junlong Guo, Yunlong Yang, Yujia Wei, Bo Huang, Xiujuan Chai, Ming Zhong
Summary: Citrus harvesting is a labor-intensive and time-intensive task, but the development of citrus-harvesting robots has gained attention as labor costs increase. This study presents an integrated solution for autonomous citrus-harvesting robots to overcome the challenges faced in commercializing them. It includes a localization and navigation algorithm, a visual method for estimating fruit poses, and a new end-effector design. Field evaluations showed promising results, with an overall success rate of 87.2% and an average picking time of 10.9 s/fruit. These efforts lay a solid foundation for the future commercialization of citrus-harvesting robots.
JOURNAL OF FIELD ROBOTICS
(2023)
Article
Chemistry, Physical
Zhixin Wang, Xu Liu, Mengyue Yue, Hongbo Yao, Haotian Tian, Xinru Sun, Yonghui Wu, Zongyin Huang, Dayan Ban, Haiwu Zheng
Summary: Smart agriculture faces challenges of low energy efficiency and lack of low-cost energy harvesting methods. This study presents a hybridized energy harvesting device that captures wind and solar energy for environmental energy collection. The device combines triboelectric nanogenerators and electromagnetic generators to transform motion into energy. A self-powered monitoring system and a farm peripheral security alarm system were established to achieve remote monitoring. This research demonstrates the potential of using triboelectric nanogenerators in smart agriculture applications.
Article
Chemistry, Physical
Pengfei Chen, Jie An, Sheng Shu, Renwei Cheng, Jinhui Nie, Tao Jiang, Zhong Lin Wang
Summary: The introduction of animal furs as a material for improving the triboelectric nanogenerator (TENG) significantly increases electric output, with high stability and low wear even in high humidity environments. By designing a counter-rotating structure, output efficiency is further enhanced.
ADVANCED ENERGY MATERIALS
(2021)
Article
Agriculture, Multidisciplinary
Faisal Jamil, Muhammad Ibrahim, Israr Ullah, Suyeon Kim, Hyun Kook Kahng, Do-Hyeun Kim
Summary: The Internet of Things (IoT) has been widely adopted in various smart applications. Lately, the greenhouse industry has gained attention for its ability to produce fresh agricultural products. However, labor and energy costs increase production costs. Additionally, ensuring the security and authenticity of agricultural data is a challenging problem. In this study, a blockchain-enabled optimization approach for greenhouse systems is proposed, which improves energy consumption and optimizes the greenhouse environment through prediction, optimization, and control. Experimental results show the effectiveness of the proposed system.
COMPUTERS AND ELECTRONICS IN AGRICULTURE
(2022)
Article
Chemistry, Analytical
Cedric Marco-Detchart, Carlos Carrascosa, Vicente Julian, Jaime Rincon
Summary: In recent years, there have been several studies using Artificial Intelligence (AI) techniques to enhance sustainable development in agriculture. One specific application is the automatic detection of plant diseases using deep learning models, which analyze and classify plants to detect potential diseases, enabling early detection and prevention of disease propagation. This paper proposes an Edge-AI device that can automatically detect plant diseases from images of plant leaves, aiming to design an autonomous device for the detection of possible diseases. Multiple tests have shown that this device significantly improves the robustness of classification responses to potential plant diseases.
Article
Agronomy
Tiago Domingues, Tomas Brandao, Ricardo Ribeiro, Joao C. Ferreira
Summary: With the increase of climate change, biodiversity loss, and biological invaders, the importance of conservation and pest management initiatives cannot be overstated. This study assesses the use of YOLOv5 to detect insects in yellow sticky traps, providing valuable insights for event forecasting and decision-making in agriculture fields.
Article
Agronomy
Aurora Gonzalez-Vidal, Jose Mendoza-Bernal, Alfonso P. Ramallo, Miguel Angel Zamora, Vicente Martinez, Antonio F. Skarmeta
Summary: The purpose of our work is to use artificial intelligence to support the emergence of smart greenhouses. By analyzing and predicting climate data, our method can accurately predict the temperature and humidity inside the greenhouse, providing data support for decision-making in greenhouse agriculture.
Article
Computer Science, Hardware & Architecture
Harsh Desai, Matteo Nardello, Davide Brunelli, Brandon Lucia
Summary: Batteryless image sensors offer long-life, long-range sensor deployments with low cost, which are critical for remote sensing applications. Camaroptera is the first batteryless image-sensing platform that combines energy harvesting with long-range communication, and utilizes machine learning to improve sensing effectiveness and availability.
ACM TRANSACTIONS ON EMBEDDED COMPUTING SYSTEMS
(2022)
Article
Automation & Control Systems
Enrico Tabanelli, Davide Brunelli, Andrea Acquaviva, Luca Benini
Summary: This article addresses the optimization of feature spaces and the reduction of computational and storage costs for running low-latency NILM on low-cost MCU-based meters. The experimental results demonstrate that optimizing the feature space enables edge MCU-based NILM with high accuracy, achieving a significant reduction in cost.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2022)
Article
Engineering, Electrical & Electronic
Luca Santoro, Davide Brunelli, Daniele Fontanelli
Summary: This paper presents a self-deployable ultra wideband UWB infrastructure that allows dynamic placement and extension of UWB anchor infrastructure while the robot explores a new environment. The study analyzes the uncertainty of the positioning system during the growth of the UWB infrastructure and proposes a genetic algorithm to optimize the deployment of new anchors, saving energy and resources.
IEEE SENSORS JOURNAL
(2022)
Article
Engineering, Electrical & Electronic
Felix Pino, Jessica Delgado, Giorgia Mantovani, Lucio Pancheri, Michele Bello, Daniela Fabris, Cristiano L. Fontana, Matteo Polo, Vladimir Ruiz, Davide Brunelli, Alberto Quaranta, Sandra Moretto
Summary: This work introduces a prototype of a detector assembly capable of discriminating between neutrons and gamma rays through pulse shape analysis. It utilizes SiPM technology and new plastics with excellent neutron/gamma-ray discrimination capabilities. The device's potential applications in nuclear physics experiments and radiation monitoring are discussed, along with performance comparisons between SiPM and standard photomultiplier read-out configurations.
IEEE TRANSACTIONS ON NUCLEAR SCIENCE
(2022)
Article
Computer Science, Hardware & Architecture
Andrea Albanese, Matteo Nardello, Davide Brunelli
Summary: This paper presents a modular and generic system that can control UAVs by evaluating vision-based machine learning tasks directly inside the resource-constrained UAV. Two different vision-based navigation configurations were tested and demonstrated, and it was shown that moving to edge computing reduces energy requirement without sacrificing service quality.
SUSTAINABLE COMPUTING-INFORMATICS & SYSTEMS
(2022)
Article
Engineering, Electrical & Electronic
Luca Gemma, Martino Bernard, Davide Brunelli
Summary: Photonic Integrated Chips (PICs) are emerging as a solution for the basic building blocks of quantum computers. This paper presents a method for easy setup and efficient architecture to optimize multiple outputs of a PIC. The proposed solution can be incorporated into an automation tool for tuning and verifying on- and off-chip detectors.
IEEE JOURNAL ON EMERGING AND SELECTED TOPICS IN CIRCUITS AND SYSTEMS
(2022)
Article
Computer Science, Hardware & Architecture
Alessio Burrello, Giovanni Zara, Luca Benini, Davide Brunelli, Enrico Macii, Massimo Poncino, Daniele Jahier Pagliari
Summary: Traffic Load Estimation (TLE) is an important task in public road infrastructures. Current approaches using dedicated sensors or smartphone sensors have limitations. Recent research suggests that using networks of accelerometers already installed for Structural Health Monitoring (SHM) purposes is a promising alternative. In this work, a supervised learning approach is proposed for TLE using SHM sensors. Smart camera recordings are used to label acceleration data and train a machine learning model to estimate vehicle count. The results show that the proposed approach achieves high accuracy, with a significant error reduction compared to previous unsupervised solutions.
SUSTAINABLE COMPUTING-INFORMATICS & SYSTEMS
(2022)
Article
Engineering, Electrical & Electronic
Andrea Albanese, Matteo Nardello, Gianluca Fiacco, Davide Brunelli
Summary: The article introduces an innovative sensor system with three MCU-based tinyML cameras for automatic artifact and anomaly detection in plastic components. Local data processing with tinyML reduces data transmission to a few bytes. Results show that both MobileNetV2 and SqueezeNet CNN architectures achieve 99% classification accuracy while maintaining suitable real-time performance on resource-constrained microcontrollers.
IEEE SENSORS JOURNAL
(2023)
Article
Engineering, Electrical & Electronic
Alessandro Torrisi, Kasim Sinan Yildirim, Davide Brunelli
Summary: This article presents fundamental hardware circuitry that enables reliable intermittent communications over wireless batteryless node networks. It emphasizes two main mechanisms that ensure energy awareness and reliability: energy status-sharing and synchronized operation. Novel low-power and self-sustainable plug-and-play circuits are introduced to support these mechanisms.
JOURNAL OF LOW POWER ELECTRONICS AND APPLICATIONS
(2022)
Article
Engineering, Electrical & Electronic
Luca Santoro, Matteo Nardello, Davide Brunelli, Daniele Fontanelli
Summary: The ultrawideband (UWB) radio technology is being widely used for indoor positioning systems. Different algorithms are being researched to find the best implementation in terms of scalability, refresh rate, and energy requirements. The downlink time difference of arrival (DTDoA) is considered a promising technique for tracking assets with high measurement update rate. This article proposes a DTDoA model and validates it using UWB data, achieving a maximum 30 cm uncertainty for the UWB indoor positioning system.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2023)
Proceedings Paper
Automation & Control Systems
Luca Santoro, Matteo Nardello, Marco Calliari, William Cechin Guarienti, Giordano Luchi, Daniele Fontanelli, Davide Brunelli
Summary: Thanks to the development of compact and microsized Unmanned Aerial Vehicles (UAVs), their use in dynamic and complex environments is becoming increasingly common. This paper presents a Leader-Follower application for Human-Robot interaction using low-cost UWB radio. The system performance was assessed and showed good accuracy, robustness, and safety.
2022 IEEE INTERNATIONAL SYMPOSIUM ON ROBOTIC AND SENSORS ENVIRONMENTS (ROSE)
(2022)
Proceedings Paper
Computer Science, Theory & Methods
Maria Doglioni, Luca Santoro, Matteo Nardello, Daniele Fontanelli, Davide Brunelli
Summary: This paper presents a study on a cheap ultrawide-band bistatic radar based on a commercial off-the-shelf UWB transceiver. The study confirms the feasibility of using UWB radios as components for radar development, achieving a mean error below 20 cm in estimated distance.
PROCEEDINGS OF 2022 IEEE INTERNATIONAL WORKSHOP ON METROLOGY FOR INDUSTRY 4.0 & IOT (IEEE METROIND4.0&IOT)
(2022)
Proceedings Paper
Engineering, Multidisciplinary
Luca Santoro, Matteo Nardello, Daniele Fontanelli, Davide Brunelli, Dario Petri
Summary: This paper presents a flexible and lightweight tracking system for sports players that can be used both indoor and outdoor. The system utilizes UWB positioning and inertial sensor data fusion to track players' performances in real-time, ensuring energy efficiency through Bluetooth data sharing.
2022 IEEE INTERNATIONAL WORKSHOP ON SPORT TECHNOLOGY AND RESEARCH (IEEE STAR 2022)
(2022)
Proceedings Paper
Computer Science, Theory & Methods
Luca Zanatta, Francesco Barchi, Alessio Burrello, Andrea Bartolini, Davide Brunelli, Andrea Acquaviva
Summary: Structural Health Monitoring (SHM) involves the use of low-cost MEMS accelerometers and neural networks to detect infrastructural damages in buildings. This study proposes a novel approach using Spiking Neural Networks (SNNs) for real-time monitoring, showcasing the effectiveness of LSNNs in analyzing data streams.
2021 IEEE INTERNATIONAL WORKSHOP ON METROLOGY FOR INDUSTRY 4.0 & IOT (IEEE METROIND4.0 & IOT)
(2021)
