scholarly journals Drones as internet of video things front-end sensors: challenges and opportunities

2021 ◽  
Vol 1 (1) ◽  
Author(s):  
Chang Wen Chen
Keyword(s):  
Sensor Data ◽  
Future Research ◽  
Operational Mode ◽  
Research Directions ◽  
Visual Sensors ◽  
Front End ◽  
Challenges And Opportunities ◽  
Acquisition Information ◽  
Future Research Directions ◽  
Technical Challenges

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.

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

2022 ◽  
Vol 8 ◽  
Author(s):  
Zhongkui Wang ◽  
Shinichi Hirai ◽  
Sadao Kawamura
Keyword(s):  
Low Cost ◽  
Food Products ◽  
Future Research ◽  
Food Handling ◽  
Research Directions ◽  
Fundamental Information ◽  
Food Recognition ◽  
Challenges And Opportunities ◽  
Future Research Directions ◽  
End Effectors

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.

Integrating Odor Sensing in Robotics

2018 ◽  
pp. 224-243
Author(s):  
Alauddin Yousif Al-Omary
Keyword(s):  
Mobile Robot ◽  
Mobile Robots ◽  
Chemical Sensors ◽  
Mobile Robotics ◽  
Future Research ◽  
Research Directions ◽  
The Future ◽  
The Status ◽  
Future Research Directions ◽  
Technical Challenges

In this chapter, the benefit of equipping the robot with odor sensors is investigated. The chapter addresses the types of tasks the mobile robots can accomplish with the help of olfactory sensing capabilities, the technical challenges in mobile robot olfaction, the status of mobile robot olfaction. The chapter also addresses simple and complex electronic olfaction sensors used in mobile robotics, the challenge of using chemical sensors, the use of many types of algorithms for robot olfaction, and the future research directions in the field of mobile robot olfaction.

scholarly journals Machine learning for energy-water nexus: challenges and opportunities

2018 ◽  
Vol 2 (3) ◽  
pp. 228-267 ◽  
Author(s):  
Zaidi ◽  
Chandola ◽  
Allen ◽  
Sanyal ◽  
Stewart ◽  
...  
Keyword(s):  
Machine Learning ◽  
Energy Systems ◽  
Machine Learning Techniques ◽  
Future Research ◽  
Technological Advancement ◽  
Research Directions ◽  
Learning Techniques ◽  
Challenges And Opportunities ◽  
Future Research Directions ◽  
System Sustainability

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.

A Survey of Multimedia Recommender Systems: Challenges and Opportunities

2017 ◽  
Vol 11 (03) ◽  
pp. 411-428 ◽  
Author(s):  
Mouzhi Ge ◽  
Fabio Persia
Keyword(s):  
Multimedia Information ◽  
Recommender Systems ◽  
Recommender System ◽  
Future Research ◽  
Research Directions ◽  
Research Challenges ◽  
Challenges And Opportunities ◽  
Future Research Directions ◽  
Research Challenge

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.

scholarly journals Pre-service Teachers with Disabilities: Challenges and Opportunities for Directors of Student Teaching in Western Canada

2017 ◽  
Vol 8 (3) ◽  
Author(s):  
Laura Sokal ◽  
Debra Woloshyn ◽  
Alina Wilson
Keyword(s):  
Teacher Education ◽  
Student Teaching ◽  
Future Research ◽  
Western Canada ◽  
Research Directions ◽  
Canadian Universities ◽  
Challenges And Opportunities ◽  
Future Research Directions ◽  
Practicum Experiences ◽  
Canadian Research

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.

scholarly journals Brainware Computing: Concepts, Scopes and Challenges

2021 ◽  
Vol 11 (11) ◽  
pp. 5303
Author(s):  
Eui-Nam Huh ◽  
Md Imtiaz Hossain
Keyword(s):  
Service Oriented Architecture ◽  
Edge Computing ◽  
Future Research ◽  
Research Directions ◽  
High Performing ◽  
Domain Specific ◽  
Challenges And Opportunities ◽  
Service Oriented ◽  
Future Research Directions ◽  
Service Application

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.

Reexamining Social Media and Socioemotional Well-Being Among Adolescents Through the Lens of the COVID-19 Pandemic: A Theoretical Review and Directions for Future Research

2021 ◽  
pp. 174569162110141
Author(s):  
Jessica L. Hamilton ◽  
Jacqueline Nesi ◽  
Sophia Choukas-Bradley
Keyword(s):  
Social Media ◽  
Media Use ◽  
Well Being ◽  
Future Research ◽  
Social Media Use ◽  
Research Directions ◽  
Psychological Science ◽  
Challenges And Opportunities ◽  
Future Research Directions ◽  
Key Aspects

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.

scholarly journals Sensor-Based Control for Collaborative Robots: Fundamentals, Challenges, and Opportunities

2021 ◽  
Vol 14 ◽  
Author(s):  
Andrea Cherubini ◽  
David Navarro-Alarcon
Keyword(s):  
Integration Method ◽  
Control Level ◽  
Direct Interaction ◽  
Future Research ◽  
Open Problems ◽  
Research Directions ◽  
Heterogeneous Sensors ◽  
Challenges And Opportunities ◽  
Potential Applications ◽  
Future Research Directions

The objective of this paper is to present a systematic review of existing sensor-based control methodologies for applications that involve direct interaction between humans and robots, in the form of either physical collaboration or safe coexistence. To this end, we first introduce the basic formulation of the sensor-servo problem, and then, present its most common approaches: vision-based, touch-based, audio-based, and distance-based control. Afterwards, we discuss and formalize the methods that integrate heterogeneous sensors at the control level. The surveyed body of literature is classified according to various factors such as: sensor type, sensor integration method, and application domain. Finally, we discuss open problems, potential applications, and future research directions.

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