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Human activity recognition using binary sensors: A systematic review

INFORMATION FUSION 2025年 115卷

作者： Khan, Muhammad Toaha Raza Ever, Enver Eraslan, Sukru Yesilada, Yeliz Middle East Tech Univ Dept Comp Engn Northern Cyprus Campus TR-99738 Guzelyurt Turkiye

Human activity recognition (HAR) is an emerging area of study and research field that explores the development of automated systems to identify and categorize human activities using data collected from various sensors. In the field of Human Activity Recognition (HAR), binary sensors offer a distinct approach by providing simpler on/off readings to indicate the presence of events such as door openings or light switch activations. Compared to other sensors used for HAR, binary sensors have several advantages, including lower cost, low power consumption, ease of installation, and privacy preservation. For instance, they can be effectively used in smart homes to detect when someone enters or leaves a room without user input. This study presents a systematic review of the state-of-the-art methods and techniques for HAR using binary sensors. We comprehensively consider five crucial aspects: data collection methods, preprocessing techniques, feature extraction and fusion strategies, classification algorithms, and evaluation metrics. Furthermore, we identify the gaps and limitations of the existing studies and provide directions for future research. This comprehensive and up-to-date review can serve as a valuable reference for researchers and practitioners in the field of HAR using binary sensors.

关键词： Human activity recognition (HAR) binary sensors Sensor data Machine learning Data analysis Pattern recognition Smart homes

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Recursive State Estimation for Discrete-Time Nonlinear Systems With binary sensors: A Locally Minimized Variance Approach

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IEEE TRANSACTIONS ON AUTOMATIC CONTROL 2024年第9期69卷 6317-6324页

作者： Huang, Yi-Bo Wang, Zidong He, Yong Wu, Min Zhejiang Univ Coll Control Sci & Engn Hangzhou 310027 Peoples R China Brunel Univ London Dept Comp Sci Uxbridge UB8 3PH England China Univ Geosci Sch Automat Wuhan 430074 Peoples R China Hubei Key Lab Adv Control & Intelligent Automat Co Wuhan 430074 Peoples R China Minist Educ Engn Res Ctr Intelligent Technol Geoexplorat Wuhan 430074 Peoples R China

In this article, the locally minimized-variance state estimation problem is investigated for a class of discrete-time nonlinear systems with Lipschitz nonlinearities and binary sensors. The output of each binary sensor takes two possible values (e.g., 0 and 1) in accordance with whether the sensed variable surpasses a prescribed threshold or not. The purpose of this article is to design a state estimation algorithm such that an upper bound of the estimation error covariance is firstly guaranteed and then minimized at each sampling instant by properly designing the estimator gain. The valid information of sensed variables is extracted from binary measurements, and a novel state estimator is constructed in a recursive form, which is suitable for online computations. Moreover, a sufficient condition is established to ensure the exponential boundedness of the prediction error in the mean square sense. Finally, two examples are presented to verify the effectiveness of the proposed method.

关键词： sensors Sensor systems State estimation Upper bound Nonlinear systems Signal processing algorithms Measurement uncertainty binary sensors difference equations nonlinear systems recursive state estimation variance constraints

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Non-Intrusive Monitoring and Detection of Mobility Loss in Older Adults Using binary sensors

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sensors 2025年第9期25卷 2755-2755页

作者： Susnea, Ioan Pecheanu, Emilia Cocu, Adina Istrate, Adrian Anghel, Catalin Iacobescu, Paul Univ Dunarea De Jos Galati Dept Comp & Informat Technol Galati 800008 Romania

(1) Background and objective: Mobility is crucial for healthy aging, and its loss significantly impacts the quality of life, healthcare costs, and mortality among older adults. Clinical mobility assessment methods, though precise, are resource-intensive and economically impractical, and most of the existing solutions for automatic detection of mobility anomalies are either obtrusive or improper for long time monitoring. This study explores the feasibility of using non-intrusive, low-cost binary sensors for continuous, remote detection of mobility anomalies in older adults, aiming to identify both sudden mobility events and gradual mobility loss. (2) Method: The study utilized publicly available datasets (CASAS Aruba and HH120) containing annotated activity data recorded from binary sensors installed in residential environments. After data preprocessing-including filtering irrelevant sensor events and aggregation into behaviorally meaningful places (BMPs)-a time series forecasting model (Prophet) was used to predict normal mobility patterns. A fuzzy inference module analyzed deviations between observed and predicted sensor data to determine the probability of mobility anomalies. (3) Results: The system effectively identified periods of prolonged inactivity indicative of potential falls or other mobility disruptions. Preliminary evaluation indicated a detection rate of approximately 77-81% for point mobility anomalies, with a false positive rate ranging from 12 to 16%. Additionally, the approach successfully detected simulated gradual declines in mobility (1% per day reduction), evidenced by statistically significant regression trends in activity levels over time. (4) Conclusions: The study argues that non-intrusive binary sensors, combined with lightweight forecasting models and fuzzy inference, may provide a practical and scalable solution for detecting mobility anomalies in older adults. Although performance can be further enhanced through improved data preprocessi

关键词： mobility loss binary sensors anomaly detection time series forecasting behaviorally meaningful places

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Secure Particle Filtering for Cyber-Physical Systems With binary sensors Under Multiple Attacks

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IEEE SYSTEMS JOURNAL 2022年第1期16卷 603-613页

作者： Song, Weihao Wang, Zidong Wang, Jianan Alsaadi, Fuad E. Shan, Jiayuan Beijing Inst Technol Sch Aerosp Engn Beijing 100081 Peoples R China Brunel Univ London Dept Comp Sci Uxbridge UB8 3PH Middx England King Abdulaziz Univ Fac Engn Dept Elect & Comp Engn Jeddah 21589 Saudi Arabia

This article is concerned with the secure particle filtering problem for a class of discrete-time nonlinear cyber-physical systems with binary sensors in the presence of non-Gaussian noises and multiple malicious attacks. The multiple attacks launched by the adversaries, which take place in a random manner, include the denial-of-service attacks, the deception attacks, and the flipping attacks. Three sequences of Bernoulli-distributed random variables with known probability distributions are employed to describe the characteristics of the random occurrence of the multiple attacks. The raw or corrupted measurements are transmitted to sensors, whose outputs are binary according to engineering practice. A modified likelihood function is constructed to compensate for the influence of the randomly occurring multiple attacks by introducing the random occurrence probability information into the design process. Subsequently, a secure particle filter is proposed based on the constructed likelihood function. Finally, a moving target tracking application is elaborated to verify the viability of the proposed secure particle filtering algorithm.

关键词： sensors Probability density function Stochastic processes Sensor systems Sensor phenomena and characterization Physical layer Particle measurements binary sensors cyber-physical systems randomly occurring attacks secure particle filtering target tracking

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Distributed Estimation for Interconnected Dynamic Systems Under binary sensors

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IEEE sensors JOURNAL 2022年第13期22卷 13153-13161页

作者： Yan, Xinhao Chen, Bo Hu, Zhongyao Zhejiang Univ Technol Dept Automat Hangzhou 310023 Peoples R China Zhejiang Univ Technol Inst Cyberspace Secur Hangzhou 310023 Peoples R China

This paper is concerned with the distributed state estimation problem for a class of interconnected dynamic systems, where several binary sensors are deployed to observe each subsystem. The judgement of switching instant for binary sensor is based on the certain estimates and sensed variables. In this case, two innovation sequences which combine thresholds and state estimates are given to extract valid information from binary measurement. Then, a distributed recursive estimator is given on the basis of weighting fusion criteria and bounded recursive optimization. The interconnected gains of state estimator are designed by minimizing the impacts of neighboring terms, while the optimal local gains and weighting fusion matrices are designed by constructing convex optimization problems. Moreover, the asymptotic stability of squared estimation error is proved by means of sequential analysis. Finally, two illustrative examples are employed to show the effectiveness of the proposed methods.

关键词： sensors Estimation Symmetric matrices Sparse matrices Kalman filters Switches Sensor systems Interconnected systems distributed estimation binary sensors bounded noises

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Optimal Design for Modulated binary sensors

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IEEE sensors JOURNAL 2022年第17期22卷 17224-17233页

作者： Olteanu, Alina Lu, Longxiang Xiao, Yang Liang, Wei Univ Montevallo Dept Biol Chem Math & Comp Sci Montevallo AL 35115 USA Chinese Acad Sci Shenyang Inst Automat State Key Lab Robot Shenyang 110016 Peoples R China Chinese Acad Sci Key Lab Networked Control Syst Shenyang 110016 Peoples R China Chinese Acad Sci Inst Robot Shenyang 110016 Peoples R China Chinese Acad Sci Inst Intelligent Mfg Shenyang 110016 Peoples R China Univ Chinese Acad Sci Beijing 100190 Peoples R China Univ Alabama Dept Comp Sci Tuscaloosa AL 35487 USA Chinese Acad Sci Shenyang Inst Automat Shenyang 110016 Peoples R China Chinese Acad Sci Shenyang Inst Automat Key Lab Networked Control Syst Shenyang 110016 Peoples R China Chinese Acad Sci Inst Robot Shenyang 110169 Peoples R China Chinese Acad Sci Inst Intelligent Mfg Shenyang 110169 Peoples R China

A paramount factor limiting the applications of binary sensors is these senors' on-off property outputting binary digits of "0" or "1". To overcome this limitation, modulators or obscurants are added to enhance the sensing ability of binary sensors and render them usable in applications such as multi-target tracking and human activity recognition. Obscurants segment the field of interest into subregions and distinguish each subregion by a list of sensor states called signatures. This paper studies two placement scenarios in a two-dimensional planar graph. In the first scenario, we prove upper and lower bounds on the maximum number of achievable signatures. In the second scenario, starting from the placement of sensors and obscurants in which the maximum number of signatures is achievable, we propose a novel mathematical model based on four main metrics: the object space size, the sensor space size, the obscurant space size, and the sizes of individual obscurants. We find the minimum and maximum radiuses that bound the object detection area given the number and sizes of sensors and obscurants. We derive the obscurant space size as a function of the object space size and the size of individual obscurants. We also provide a linear relationship formula between the obscurant space radius, the sensor space radius, and the obscurants' radiuses and conduct modeling experiments to study the relationship between these metrics. Finally, we deduct an explicit formula for the maximum obscurant space size for the sensor space and the individual obscurant sizes.

关键词： sensors Sensor systems Sensor arrays Modulation Shape Automation Robot sensing systems binary sensors sensor array reference structure sensor deployment optimization modulator obscurant signature theoretical analysis

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The Maximum Number of Cells With Modulated binary sensors

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IEEE sensors JOURNAL 2021年第9期21卷 11061-11074页

作者： Luo, Longxiang Xiao, Yang Liang, Wei Chinese Acad Sci Shenyang Inst Automat State Key Lab Robot Shenyang Peoples R China Chinese Acad Sci Key Lab Networked Control Syst Shenyang 110016 Peoples R China Chinese Acad Sci Inst Robot Shenyang 110169 Peoples R China Chinese Acad Sci Inst Intelligent Mfg Shenyang 110169 Peoples R China Univ Chinese Acad Sci Beijing 100049 Peoples R China Univ Alabama Dept Comp Sci Tuscaloosa AL 35487 USA

Due to the low cost and good privacy protection of binary sensors, there are many applications of binary sensors. To enhance the spatial awareness of binary sensors, researchers utilize modulators to modulate views of sensors into visible and invisible regions so that the monitoring space is segmented into small cells identified by signatures. When a warm object moves in these cells, its location or moving trajectory can be acquired more accurately with modulators than without modulators. Accordingly, the maximum number of cells (MNC) in a deployment determines partially the maximal spatial awareness of the binary sensor system. In this paper, we provide a theoretical study of the MNC, given the number of sensors and the number of modulators. We also find the sufficient and necessary conditions to achieve the MNC so that we provide the reasons why deployment cannot obtain the MNC. These conditions can guide researchers to design the MNC deployments. Furthermore, we provide a method to calculate the number of cells when a deployment sometime cannot obtain the MNC. Our experiments provide deep insights into the influences of those conditions on the MNC and the MNC on the spatial awareness of binary sensor systems.

关键词： sensors Modulation Sensor systems Shape Monitoring Sensor arrays Trajectory Internet of Things (IoT) binary sensors sensor deployment sensor array spatial awareness the maximum number of cells

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Fusion estimation under binary sensors

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AUTOMATICA 2020年第0期115卷 108861-000页

作者： Zhang, Yuchen Chen, Bo Yu, Li Zhejiang Univ Technol Dept Automat Hangzhou 310023 Peoples R China Zhejiang Univ Technol Inst Cyberspace Secur Hangzhou 310023 Peoples R China

binary sensors compress the measurement information into two possible values as output and have found applications in many fields such as medical monitoring, environment monitoring and localization. This paper is concerned with the fusion estimation problem for a class of binary sensor systems with bounded noises, where the monitored physical process is described by time-varying state-space models. Since binary sensors only provide the valid information at the switching instant, a novel uncertain measurement model is proposed to characterize this feature. Then, by constructing an upper bound of fusion/estimation error at each time, convex optimization problems are established in terms of linear matrix inequalities to design stable centralized and distributed fusion estimators. An illustrative example is given to show the effectiveness of the proposed methods. (C) 2020 Elsevier Ltd. All rights reserved.

关键词： Fusion estimation binary sensors Bounded noises Convex optimization

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Distributed fusion Kalman filtering under binary sensors

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INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL 2020年第6期30卷 2570-2578页

作者： Zhang, Yuchen Chen, Bo Yu, Li Zhejiang Univ Technol Dept Automat Hangzhou 310023 Peoples R China Zhejiang Univ Technol Inst Cyberspace Secur Hangzhou 310023 Peoples R China

binary sensors are special sensors that only transmit one-bit information at each time and have been widely applied to environmental awareness and medical monitoring. This paper is concerned with the distributed fusion Kalman filtering problem for a class of binary sensor systems. A novel uncertainty approach is proposed to better extract valid information from binary sensors at switching instant. By minimizing a local estimation error covariance, the local robust Kalman estimates are firstly obtained. Then, the distributed fusion Kalman filter is designed by resorting to the covariance intersection fusion criterion. Finally, a blood oxygen content model is employed to show the effectiveness of the proposed methods.

关键词： binary sensors fusion estimation Kalman filtering

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Implementing a Semi-causal Domain-Specific Language for Context Detection over binary sensors 2018

Implementing a Semi-causal Domain-Specific Language for Cont...

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17th ACM SIGPLAN International Conference on Generative Programming - Concepts and Experiences (GPCE) part of the SPLASH Collection of Conferences and Workshops

作者： Volanschi, Nic Serpette, Bernard Consel, Charles Inria Bordeaux Talence France Bordeaux INP Talence France

ISBN: (纸本)9781450360456

In spite of the fact that many sensors in use today are binary (i.e. produce only values of 0 and 1), and that useful context-aware applications are built exclusively on top of them, there is currently no development approach specifically targeted to binary sensors. Dealing with notions of state and state combinators, central to binary sensors, is tedious and error-prone in current approaches. For instance, developing such applications in a general programming language requires writing code to process events, maintain state and perform state transitions on events, manage timers and/or event histories. In another paper, we introduced a domain specific language (DSL) called Allen, specifically targeted to binary sensors. Allen natively expresses states and state combinations, and detects contexts on line, on incoming streams of binary events. Expressing state combinations in Allen is natural and intuitive due to a key ingredient: semi-causal operators. That paper focused on the concept of the language and its main operators, but did not address its implementation challenges. Indeed, online evaluation of expressions containing semi-causal operators is difficult, because semicausal sub-expressions may block waiting for future events, thus generating unknown values, besides 0 and 1. These unknown values may or may not propagate to the containing expressions, depending on the current value of the other arguments. This paper presents a compiler and runtime for the Allen language, and shows how they implement its state combining operators, based on reducing complex expressions to a core subset of operators, which are implemented natively. We define several assisted living applications both in Allen and in a general scripting language. We show that the former are much more concise in Allen, achieve more effective code reuse, and ease the checking of some domain properties.

关键词： domain-specific languages binary sensors context awareness

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