scholarly journals Challenges and Opportunities in Robotic Food Handling: A Review

2022 ◽  
Vol 8 ◽  
Author(s):  
Zhongkui Wang ◽  
Shinichi Hirai ◽  
Sadao Kawamura

Despite developments in robotics and automation technologies, several challenges need to be addressed to fulfill the high demand for automating various manufacturing processes in the food industry. In our opinion, these challenges can be classified as: the development of robotic end-effectors to cope with large variations of food products with high practicality and low cost, recognition of food products and materials in 3D scenario, better understanding of fundamental information of food products including food categorization and physical properties from the viewpoint of robotic handling. In this review, we first introduce the challenges in robotic food handling and then highlight the advances in robotic end-effectors, food recognition, and fundamental information of food products related to robotic food handling. Finally, future research directions and opportunities are discussed based on an analysis of the challenges and state-of-the-art developments.

2018 ◽  
Vol 2 (3) ◽  
pp. 228-267 ◽  
Author(s):  
Zaidi ◽  
Chandola ◽  
Allen ◽  
Sanyal ◽  
Stewart ◽  
...  

Modeling the interactions of water and energy systems is important to the enforcement of infrastructure security and system sustainability. To this end, recent technological advancement has allowed the production of large volumes of data associated with functioning of these sectors. We are beginning to see that statistical and machine learning techniques can help elucidate characteristic patterns across these systems from water availability, transport, and use to energy generation, fuel supply, and customer demand, and in the interdependencies among these systems that can leave these systems vulnerable to cascading impacts from single disruptions. In this paper, we discuss ways in which data and machine learning can be applied to the challenges facing the energy-water nexus along with the potential issues associated with the machine learning techniques themselves. We then survey machine learning techniques that have found application to date in energy-water nexus problems. We conclude by outlining future research directions and opportunities for collaboration among the energy-water nexus and machine learning communities that can lead to mutual synergistic advantage.


Sensors ◽  
2019 ◽  
Vol 19 (8) ◽  
pp. 1793 ◽  
Author(s):  
Yousaf Bin Zikria ◽  
Sung Won Kim ◽  
Oliver Hahm ◽  
Muhammad Khalil Afzal ◽  
Mohammed Y. Aalsalem

Internet of Things (IoT) is rapidly growing and contributing drastically to improve the quality of life. Immense technological innovations and growth is a key factor in IoT advancements. Readily available low cost IoT hardware is essential for continuous adaptation of IoT. Advancements in IoT Operating System (OS) to support these newly developed IoT hardware along with the recent standards and techniques for all the communication layers are the way forward. The variety of IoT OS availability demands to support interoperability that requires to follow standard set of rules for development and protocol functionalities to support heterogeneous deployment scenarios. IoT requires to be intelligent to self-adapt according to the network conditions. In this paper, we present brief overview of different IoT OSs, supported hardware, and future research directions. Therein, we provide overview of the accepted papers in our Special Issue on IoT OS management: opportunities, challenges, and solution. Finally, we conclude the manuscript.


2017 ◽  
Vol 11 (03) ◽  
pp. 411-428 ◽  
Author(s):  
Mouzhi Ge ◽  
Fabio Persia

Multimedia information has been extensively growing from a variety of sources such as cameras or video recorders. In order to select the useful multimedia objects, multimedia recommender system has been emerging as a tool to help users choose which multimedia objects might be interesting for them. However, given the complexity of multimedia objects, it is challenging to provide effective multimedia recommendations. In this paper, we therefore conduct a survey in both the multimedia information system and recommender system communities. We further focus on the works that span the two communities, especially the research on multimedia recommender systems. Based on our review, we propose a set of research challenges, which can be used to implicate the future research directions for multimedia recommender systems. For each research challenge, we have also provided the insights of how to perform the follow-up research.


Author(s):  
Jungwon Seo ◽  
Jamie Paik ◽  
Mark Yim

This article reviews the current state of the art in the development of modular reconfigurable robot (MRR) systems and suggests promising future research directions. A wide variety of MRR systems have been presented to date, and these robots promise to be versatile, robust, and low cost compared with other conventional robot systems. MRR systems thus have the potential to outperform traditional systems with a fixed morphology when carrying out tasks that require a high level of flexibility. We begin by introducing the taxonomy of MRRs based on their hardware architecture. We then examine recent progress in the hardware and the software technologies for MRRs, along with remaining technical issues. We conclude with a discussion of open challenges and future research directions.


Author(s):  
Laura Sokal ◽  
Debra Woloshyn ◽  
Alina Wilson

In response to the lack of Canadian research about the practicum experiences of pre-service teachers with disabilities, a survey of ten Directors of Student Teaching in Western Canadian universities was conducted and revealed both strengths and challenges in current practices. Recommendations for teacher education are explored, and several future research directions are highlighted. En réponse à l’absence de recherche sur les expériences de stage des enseignants en formation souffrant d’invalidité, un sondage a été effectué auprès de dix directeurs de stagiaires dans des universités de l’Ouest du Canada. Le sondage a révélé à la fois les points forts et les défis présentés par les pratiques actuelles. Des recommandations pour la formation des enseignants sont explorées et plusieurs futurs axes de recherche sont présentés.


2021 ◽  
Vol 1 (1) ◽  
Author(s):  
Chang Wen Chen

AbstractInternet of Video Things (IoVT) has become an emerging class of IoT systems that are equipped with visual sensors at the front end. Most of such visual sensors are fixed one whereas the drones are considered flying IoT nodes capable of capturing visual data continuously while flying over the targets of interest. With such a dynamic operational mode, we can imagine significant technical challenges in sensor data acquisition, information transmission, and knowledge extraction. This paper will begin with an analysis on some unique characteristics of IoVT systems with drones as its front end sensors. We shall then discuss several inherent technical challenges for designing drone-based IoVT systems. Furthermore, we will present major opportunities to adopt drone-based IoVT in several contemporary applications. Finally, we conclude this paper with a summary and an outlook for future research directions.


Author(s):  
Konstantinos B. Baltzis

A significant part of worldwide energy is consumed by the ICT infrastructure with wireless sector to be among the main contributors to this consumption. As a result, the rising energy costs and increasing carbon footprint of operating wireless communication networks have generated a keen interest in the design and development of “green” networks, that is, networks characterized by energy efficiency, reduced CO2 emissions, and low cost deployment. In this article, we discuss current issues and trends in green wireless networking. We explain the motivation behind it, discuss basic principles, review current trends in the field, and highlight upcoming challenges and future research directions. The aforementioned issues have been treated in detail in the scientific literature. However, the present study overviews current and future trends in green wireless networking with focus on providing an insight into the field that will be useful not only for experts but for non-specialists also.


Author(s):  
Kai Xu ◽  
Yong Chen

The mask-image-projection-based stereolithography process (MIP-SL) using a digital micromirror device (DMD) is an area-processing-based additive manufacturing (AM) process. In the MIP-SL process, a set of mask images are dynamically projected onto a resin surface to selectively cure liquid resin into layers of an object. Consequently, the MIP-SL process can be faster with a lower cost than the laser-based stereolithography apparatus (SLA) process. Currently an increasing number of companies are developing low-cost 3D printers based on the MIP-SL process. However, current commercially available MIP-SL systems are mostly based on Acrylate resins, which have larger shrinkages when compared to epoxy resins used in the laser-based SLA process. Consequently, controlling the shrinkage-related shape deformation in the MIP-SL process is challenging. In this research, we evaluate different mask image exposing strategies for building part layers and their effects on the deformation control in the MIP-SL process. Accordingly, a mask image planning method and related algorithms have been developed for a given computer-aided design (CAD) model. The planned mask images have been tested by using a commercial MIP-SL machine. The experimental results illustrate that our method can effectively reduce the deformation by as much as 32%. A discussion on the advantages and disadvantages of the mask image planning method and future research directions are also presented.


2021 ◽  
Vol 11 (11) ◽  
pp. 5303
Author(s):  
Eui-Nam Huh ◽  
Md Imtiaz Hossain

Over the decades, robotics technology has acquired sufficient advancement through the progression of 5G Internet, Artificial Intelligence (AI), Internet of Things (IoT), Cloud, and Edge Computing. Though nowadays, Cobot and Service Oriented Architecture (SOA) supported robots with edge computing paradigms have achieved remarkable performances in diverse applications, the existing SOA robotics technology fails to develop a multi-domain expert with high performing robots and demands improvement to Service-Oriented Brain, SOB (including AI model, driving service application and metadata) enabling robot for deploying brain and a new computing model with more scalability and flexibility. In this paper, instead of focusing on SOA and Robot as a Service (RaaS) model, we propose a novel computing architecture, addressed as Brainware Computing, for driving multiple domain-specific brains one-at-a-time in a single hardware robot according to the service, addressed as Brain as a Service (BaaS). In Brainware Computing, each robot can install and remove the virtual machine, which contains SOB and operating applications from the nearest edge cloud. Secondly, we provide an extensive explanation of the scope and possibilities of Brainware Computing. Finally, we demonstrate several challenges and opportunities and then concluded with future research directions in the field of Brainware Computing.


2021 ◽  
pp. 174569162110141
Author(s):  
Jessica L. Hamilton ◽  
Jacqueline Nesi ◽  
Sophia Choukas-Bradley

Social media has rapidly transformed the ways in which adolescents socialize and interact with the world, which has contributed to ongoing public debate about whether social media is helping or harming adolescents. The COVID-19 pandemic has magnified both the challenges and opportunities of adolescents’ social-media use, which necessitates revisiting the conversation around teens and social media. In this article, we discuss key aspects of adolescent social-media use and socioemotional well-being and outline how these issues may be amplified in the context of the COVID-19 pandemic. We use this as a springboard to outline key future research directions for the field, with the goal of moving away from reductionist approaches and toward a more nuanced perspective to understand the who, what, and when of social-media use and its impact on adolescent well-being. We conclude with a commentary on how psychological science can inform the translation of research to provide evidence-based recommendations for adolescent social-media use.


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