Chapter 6
Applied Machine Vision and IoT
V. García,
N. Sánchez,
J.A. Rodrigo,
J.M. Menéndez,
J. Lalueza,
V. García
Visiona Ingeniería de Proyectos, C/Artistas 39, Madrid, Spain
Search for more papers by this authorN. Sánchez
Visiona Ingeniería de Proyectos, C/Artistas 39, Madrid, Spain
Search for more papers by this authorJ.A. Rodrigo
Visiona Ingeniería de Proyectos, C/Artistas 39, Madrid, Spain
Search for more papers by this authorJ.M. Menéndez
Grupo de Aplicación de Telecomunicaciones Visuales, Universidad Politecnica de Madrid, Madrid, Spain
Search for more papers by this authorJ. Lalueza
Visiona Ingeniería de Proyectos, C/Artistas 39, Madrid, Spain
Search for more papers by this authorV. García,
N. Sánchez,
J.A. Rodrigo,
J.M. Menéndez,
J. Lalueza,
V. García
Visiona Ingeniería de Proyectos, C/Artistas 39, Madrid, Spain
Search for more papers by this authorN. Sánchez
Visiona Ingeniería de Proyectos, C/Artistas 39, Madrid, Spain
Search for more papers by this authorJ.A. Rodrigo
Visiona Ingeniería de Proyectos, C/Artistas 39, Madrid, Spain
Search for more papers by this authorJ.M. Menéndez
Grupo de Aplicación de Telecomunicaciones Visuales, Universidad Politecnica de Madrid, Madrid, Spain
Search for more papers by this authorJ. Lalueza
Visiona Ingeniería de Proyectos, C/Artistas 39, Madrid, Spain
Search for more papers by this authorBook Editor(s):John Davies,
Carolina Fortuna,
John Davies
BT Research and Venturing, Head of Next Generation Web Research, United Kingdom
Search for more papers by this authorCarolina Fortuna
Josef Stefan Institute, Department of Communication Systems, Ljubljana, Slovenia
Search for more papers by this authorSummary
This chapter analyzes and discusses to what extent machine vision is applicable and can benefit Internet of Things (IoT), wherein computing capability is extended to a variety of objects, devices, and sensors. It presents the fundamentals of machine vision and then proceeds to look at current trends in machine vision research and development. The chapter then looks at deep learning in the machine vision context. Given that transfer learning can generate a model for each specific task, a generic deep learning framework for improved situation awareness can be defined as part of an IoT system, where every phase of the framework should be accomplished by an element of the IoT infrastructure. The chapter finally describes three IoT use cases for machine vision technology and describes the challenges of sensing critical infrastructures, like power plants or oil pipelines, using drones, thus exploiting the latest advances in Machine Vision.
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