Recognition of cooking activities through air quality sensor data for supporting food journaling

Gerina, Federica; Massa, Silvia M.; Moi, Francesca; Recupero, Diego Reforgiato; Riboni, Daniele

doi:10.1186/s13673-020-00235-9

Cited by 13 publications

(3 citation statements)

References 38 publications

(54 reference statements)

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“…Any correlated actions of multiple 'u' are generally possible but out of the scope of this research. If there are no additional resources demanded from 'u', but time, we can use earlier defined p to modify (18) to:…”

Section: Methodsmentioning

confidence: 99%

Forecasting economic result of business logic improvements using Game Theory for modeling user scenarios

Kuzmin¹,

Станасюк²,

Berdnik³

et al. 2021

Math. Model. Comput.

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A new approach to user behavior modeling based on Game Theory was proposed. It was developed to consider initial intensity, a strategy applied, a profit gained, and resources utilized as inalienable attributes of users' behavior. The approach covers various aspects of users' motivation and rational actions, not only a statistical image of a pool's summary. Additionally, the given model is strongly connected to profit and loss parameters by operating with profit and utilized resources as parts of model inputs. The proposed model can enable efficient modeling aimed to validate an economic result of existing interfaces and assume results of new ones.

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Section: Methodsmentioning

confidence: 99%

Forecasting economic result of business logic improvements using Game Theory for modeling user scenarios

Kuzmin¹,

Станасюк²,

Berdnik³

et al. 2021

Math. Model. Comput.

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show abstract

“…In recent years, the application of AI methods to sensor data is gaining increasing interest in several applications areas [21,22,23,24]. Internet of Things [27].…”

Section: Iot-based Recognition Of Abnormal Activitiesmentioning

confidence: 99%

HealthXAI: Collaborative and explainable AI for supporting early diagnosis of cognitive decline

Khodabandehloo

Riboni

Alimohammadi

2021

Future Generation Computer Systems

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“…Sensory data analysis has several important applications in different areas, including ambient-assisted living [4,14], physical training [15,16], managing emergency situations, and automatic detection of abnormal activities in surveillance environments [17,18]; most of these applications require HAR in the first step. HAR is typically addressed as a supervised learning problem [19,20], where a mathematical model is created based on the relationship between the raw or preprocessed input data (observations) and the output data (current activity).…”

Section: Introductionmentioning

confidence: 99%

Activity Recognition in Smart Homes via Feature-Rich Visual Extraction of Locomotion Traces

2023

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The proliferation of sensors in smart homes makes it possible to monitor human activities, routines, and complex behaviors in an unprecedented way. Hence, human activity recognition has gained increasing attention over the last few years as a tool to improve healthcare and well-being in several applications. However, most existing activity recognition systems rely on cameras or wearable sensors, which may be obtrusive and may invade the user’s privacy, especially at home. Moreover, extracting expressive features from a stream of data provided by heterogeneous smart-home sensors is still an open challenge. In this paper, we investigate a novel method to detect activities of daily living by exploiting unobtrusive smart-home sensors (i.e., passive infrared position sensors and sensors attached to everyday objects) and vision-based deep learning algorithms, without the use of cameras or wearable sensors. Our method relies on depicting the locomotion traces of the user and visual clues about their interaction with objects on a floor plan map of the home, and utilizes pre-trained deep convolutional neural networks to extract features for recognizing ongoing activity. One additional advantage of our method is its seamless extendibility with additional features based on the available sensor data. Extensive experiments with a real-world dataset and a comparison with state-of-the-art approaches demonstrate the effectiveness of our method.

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Recognition of cooking activities through air quality sensor data for supporting food journaling

Cited by 13 publications

References 38 publications

Forecasting economic result of business logic improvements using Game Theory for modeling user scenarios

Forecasting economic result of business logic improvements using Game Theory for modeling user scenarios

HealthXAI: Collaborative and explainable AI for supporting early diagnosis of cognitive decline

Activity Recognition in Smart Homes via Feature-Rich Visual Extraction of Locomotion Traces

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