Chandreyee Chowdhury

• Ph. D.
• Professor (Assistant) at Jadavpur University

Recently mobile agents are used to discover services in mobile ad-hoc network (MANET) where agents travel through the network, collecting and sometimes spreading the dynamically changing service information. But it is important to investigate how reliable the agents are for this application as the dependability issues(reliability and availability)...

Nowadays there is an increasing trend of applying wireless technologies in industrial automation. However, the industrial control environment is harsher and noisier posing more stringent requirements on real-time communication. The variation in wireless signal strength with time and location, and power limitation due to battery usage make the probl...

This chapter presents a roadmap of key developments in IoT-Cloud research in the context of different application domains and its applicability to IoE. IoT can be extended to IoE, if it is possible to connect everything to the Internet. Different layers of IoT protocol stack are discussed in this chapter. In IoT, physical objects connected to the I...

In this work, the design of a robust route recommendation system is proposed based on crowdsourcing. The prevalent research challenge of crowdsourcing, that is, biased or unreliable user opinions has been addressed in the work through a multi-phased data validation framework. The client-server-based multi-tier architecture proposed in the work ensu...

Human activity recognition (HAR) from sensory data is a crucial task for a wide variety of applications. The in-built inertial sensor facilities of commercial smartphones have made the data collection process easier. However, different smartphone configurations exhibit variations in sensor readings for the same activities. Different smartphone hold...

Dimensionality reduction is an important task for Wi-Fi-based indoor localization (IL). Most such techniques do not take into account realistic data collection issues such as the presence of outliers or inconsistent fingerprint instances. These fingerprints either represent a class boundary or an outlier. Instance hardness is a measure that better...

The main purpose of indoor localization is to precisely locate users and help them navigate within an indoor area, like a building or campus, where GPS and other satellite technologies lack precision. Our methodology for achieving indoor localization has been to implement classifiers that use Received Signal Strength Indicator (RSSI) values of WiFi...

The efficacy of machine learning-based Human Activity Recognition (HAR) heavily relies on the datasets. Existing benchmark HAR datasets on smartphone accelerometer sensors provide mostly single-labeled, fine-grained activities like walking, sitting, etc. collected in lab set-up. In real life, users hardly perform an activity in isolation. Rather, t...

Due to the Covid-19 pandemic, the education system in India has changed to remote that is, online study mode. Though there are works on the effect of teaching learning on Indian students, the effect of online mode and associated mental state, particularly when the entire country is going through a crisis could not be found in the literature. Our go...

Human gait modeling with step length estimation (SLE) is not only indispensable for health monitoring of the patients with neurological disorder but also crucial part of the pedestrian dead reckoning (PDR) based localization systems. The PDR based location tracking methods, on the other hand, can be effectively used to offer the mobility solutions...

Smartphone sensor-based pedestrian dead reckoning (PDR) systems provide a viable solution to the problem of localization in an infrastructure-less area. Step detection (SD) and step length estimation (SLE), being two fundamental operations of the PDR based localization technique, have drawn many researchers’ attention in the recent time. Most of th...

Being one of the fastest growing industries in recent times, healthcare has witnessed a complete transition in the last decade. Rapid technological and communication advancements in machine learning have contributed to predict fatal diseases with datasets available from various sources. Single-layer ensemble learning has been applied in literature...

These are the below tentative table of contents but not limited. 1. Science, technology and innovation ecosystem transformation toward society 2. Society 5.0: For human security and well-being 3. Society 5.0 and Social Development 4. Human-centered artificial intelligence: Reliable, safe & trustworthy 5. Smart human-centered service systems of t...

With rapid progress in ICT, novel concepts like IoT and Industrial IoT, (IIoT) have emerged in the last decade, where the latter focuses on industrial applications such as manufacturing, agriculture, logistics, and pharmaceuticals. A significant improvement in sensor based Human Activity Recognition (HAR) is also evident especially after the upsurg...

Seamless positioning and navigation requires an integration of outdoor and indoor positioning systems. Until recently, these systems mostly function in-silos. Though GNSS has become a standalone system for outdoors, no unified positioning modality could be found for indoor environments. Wi-Fi and Bluetooth signals are popular choices though. Increa...

With the advancement in indoor localization and navigation, indoor spaces are represented using distinct forms of spatial information. Communication and interoperability among different systems comprising different technologies demand a common standardized representation. From this demand, OGC published IndoorGML as a standard spatial data model. H...

Due to their availability on commercial smartphones, WiFi, Bluetooth, and magnetometer are commonly utilized for indoor localization as indoor spaces are GPS deprived. Indoor localization falls into the category of data-intensive applications. In this domain, most of the recent solution approaches deploy machine learning (ML) and deep learning (DL)...

Human Activity Recognition (HAR) has earned a lot of importance in recent years due to its applications in various domains including smart healthcare, entertainment, surveillance applications and so on. Due to easy portability and privacy, inertial sensing based HAR has gained potential research interests. The accelerometer and gyroscope sensors de...

Recently developed IoT devices are capable of gathering, storing, and processing more data than ever before. This calls for the need for scalability. Through the use of edge computing, more processing functions can be relocated closer to where the data is gathered through the IoT devices. Here, processing tasks may be placed in the edge computing u...

p> Smartphone sensor-based pedestrian dead reckoning (PDR) systems provide a viable solution to the problem of localization in an infrastructure-less area. Step detection (SD) and step length estimation (SLE), being two fundamental operations of the PDR based localization technique, have drawn many researchers’ attention in the recent time. Most of...

p> Smartphone sensor-based pedestrian dead reckoning (PDR) systems provide a viable solution to the problem of localization in an infrastructure-less area. Step detection (SD) and step length estimation (SLE), being two fundamental operations of the PDR based localization technique, have drawn many researchers’ attention in the recent time. Most of...

This work proposes a stochastic model of the coordinator units of each wireless body area network (WBAN) in a multi-WBAN scenario. In a Smart Home environment, multiple patients can come into the vicinity of each other while each of them is wearing a WBAN configuration for monitoring body vitals. Thus, while multiple WBANs coexist, the individual W...

With the advancement in wireless sensing technology, the notion of the Internet of Things (IoT) has become ubiquitous and widely adopted due to its extensive applications in smart living. In that regard, Human Activity Recognition (HAR) is an indispensable part of intelligent systems for continuous supervision of human behavior. The design of effec...

Efficient transmission of prioritized data packets is of utmost importance for wireless body area networks (WBAN). In this paper, the problem of inter-WBAN communication with multiple edges is investigated to maximize the transmission efficiency subject to data priority and channel quality. The contribution is twofold. First, the authors jointly co...

Recently developed IoT devices are capable of gathering, storing, and processing more data than ever before. This calls for the need for scalability. Through the use of edge computing, more processing functions can be relocated closer to where the data is gathered through the IoT devices. Here, processing tasks may be placed in the Edge Computing U...

Due to their availability on commercial smartphones, WiFi, Bluetooth, and magnetometer are commonly utilized for indoor localization as indoor spaces are GPS deprived. Indoor localization falls into the category of data-intensive applications. In this domain, most of the recent solution approaches deploy MachineLearning (ML) and Deep Learning (DL)...

The rapid growth of mobile communication and pervasive computing technology has expanded the demand for location-based services in urban areas, which necessitate accurate localization and tracking of the user. Due to very poor performances of global positioning system (GPS) in indoor areas and urban canyons, various radio frequency (RF) technologie...

Wireless body area networks (WBANs) are becoming a popular and convenient mechanism for IoT-based health monitoring applications. Maintaining the energy efficiency of the nodes in WBANs without degrading network performance is one of the crucial factors for the success of this paradigm. Obtaining routes for data packets should be a dynamic decision...

Optimal selection of features leads to the increase in perceptibility of the predictor procedure and thereby in turn increases the accuracy. In the domain of WiFi-based indoor positioning, access points are a ubiquitous source of features with which the positioning process is carried out. The selection of a proper subset of access points is crucial...

Internet of Things Based Smart Healthcare (Intelligent and Secure Solutions Applying Machine Learning Techniques)

With the increasing population and diverse environment, health care data prediction plays an important role. The goal of the work is to build a system that predicts a disease accurately based on basic knowledge. With the advancement of ICT-based Healthcare systems, Wearable smart devices (WSD) play an important role in monitoring body vitals and he...

Smart handheld devices such as smartphones are capable of sensing and interacting with surrounding environments. This emerging capability of smartphones has resulted in the utilization of it as input devices and led it to be used as the default physical interface in applications of ubiquitous computing. Mobile crowdsensing is a new paradigm, which...

Human Activity Recognition through smartphones plays a crucial role in several medical state-of-affairs like patient monitoring, eldercare, and post-surgery recovery. Most of these works require precisely labeled accelerometer data for training supervised learning classifiers. Precise labeling of smartphone sensing data is difficult in real life du...

Human Activity Recognition (HAR) is an important research area that has profound applications in healthcare, security and surveillance. Starting from traditional machine learning approaches to the recently evolving deep learning techniques, researchers have exhibited significant contributions in the HAR field in the last decade. Recently, meta-heur...

IoT based Sensor network

User privacy is an important concern that should be handled in data intensive applications. Interestingly, differential privacy is a privacy model that can be applied to such datasets. This model is advantageous as it does not make any strong assumption about the adversary. In this work, we have introduced the notion of differential privacy in the...

This paper proposes effective communication strategies for Wireless Body Area Networks (WBANs) that consist of wearable or implantable sensor nodes placed in, on/around the human body to send body vitals to a sink. The main research challenges for communication strategy formulation include limited energy resources and varying link conditions. Thoug...

Indoor localization systems are extensively used to develop positioning in various public buildings, and warehouses, for localization and navigation of users, robots and/or tracking assets. Researchers have developed and worked on variegated technologies such as, Bluetooth Low Energy, motion planning, Received Signal Strength based fingerprinting a...

Indoor localization has the capability to change the way of providing location-based services in a closed environment and has more potential than that of GPS if the present shortcomings can be overcome. Thus, developing a ubiquitous Indoor Localization System (ILS) is the need of the day. WiFi-based indoor localization using smartphones is a promis...

With the wide availability of smartphone sensing and the Internet connections, mobile crowd sourcing (MCS) has become a promising paradigm for collecting opinions and providing services to the citizens. In the smart city context, crowd data, both in the form of their opinions and in the form of sensing data from their smartphones are very useful fo...

This work proposes a stochastic model of the coordinator units of each wireless body area network (WBAN) in a multi-WBAN scenario. In a Smart Home environment, multiple patients can come in vicinity of each other while each of them are wearing a WBAN configuration for monitoring of body vitals. Thus, while multiple WBAN coexists, the individual WBA...

For WiFi-based indoor localization, optimal selection of features leads to the increased perceptibility of the localization procedure. It is essential to capture the important sets of Access Points (APs) that best defines the floor map for the positioning process. To maintain sustainable localization, the selection of APs enables scaling the soluti...

The growth of world population and tremendous urbanization initiatives has posed an important challenge to sustainable agriculture. To efficiently utilize the land to yield maximum produce, IoT based smart agriculture monitoring systems are an absolute necessity today. The sensing and actuator modules deployed as part of such systems are responsibl...

The present disclosure relates to an IoT based system and method for fall detection in elderly or PD people by the means of Smartphone. In the present disclosure an onboard 3 axis accelerometer (BMI160) of a Smartphone device is used. The accelerometer collects the real time data from various movements. The values from sensor are then analyzed by t...

The Internet of Things (IoT) ecosystem is gradually changing our activities and social interactions through the wide scale of applications it offers. However, these applications rely on the networking protocol stack where the application layer of the stack is implemented differently by different applications. As a result, a variety of data represen...

Wireless Body Area Networks enable a new trend of proactive health care exploiting battery-powered wearable and/or implantable sensor nodes. The transmission of biomedical signals consumes most of the scarce energy resources in a WBAN. State-of-the-art transmission mechanisms either focus on energy efficiency or timely data delivery. However, an op...

WiFi-based indoor localization is a popular approach as most buildings and campuses are WiFi-enabled and its fingerprints are captured by smartphones carried by every individual. Due to the different WiFi sensitivity of the smartphones, an interesting challenge subject to varying ambient conditions emerges in this domain. Thus, a single supervised...

The ongoing COVID-19 pandemic has caused worldwide socioeconomic unrest, forcing governments to introduce extreme measures to reduce its spread. Being able to accurately forecast the effect of unlocking in India would allow governments to alter their policies accordingly and plan ahead. The study investigated prediction forecasts using the ARIMA mo...

In the recent past, we have witnessed the adoption of different machine learning techniques for indoor positioning applications using WiFi, Bluetooth and other technologies. The techniques range from heuristically derived hand-crafted feature-based traditional machine learning algorithms, feature selection algorithms to the hierarchically self-evol...

Smartphone based human activity monitoring and recognition play an important role in several medical applications, such as eldercare, diabetic patient monitoring, post-trauma recovery after surgery. However, it is more important to recognize the activity sequences in terms of transitions. In this work, we have designed a detailed activity transitio...

Human activity recognition (HAR) and monitoring is beneficial for many medical applications, such as eldercare and post-trauma rehabilitation after surgery. HAR models based on smartphone’s accelerometer data could provide a convenient and ubiquitous solution to this problem. However, such models are mostly concerned with identifying basic activiti...

Localization in indoor environmentPanja, Ayan Kumar is one of the major area of research in the present era.Chowdhury, Chandreyee With advancement of technology and extensiveRoy, Priya use of smartphone applicationsMallick, Sakil the requirement for development of fast reliable location based service is needed.Mondal, Sukanto RSSI fingerprinting fr...

Combination of meta-heuristics approaches and machine learning techniques have revolutionized the field of Internet of Things (IoT) based smart monitoring applications. Sensors are the eyes of IoT and hence, data analysis based on sensor fusion can explore meaningful insight in making these IoT based applications smart. Such systems can solve compl...

One of the major benefits of the Internet of Things (IoT) is its role in revolutionizing the conventional concept of healthcare which was primarily reactive in nature. By enabling applications ranging from remote health monitoring of chronic diseases to proactive wellness management, IoT infrastructure can offer improved quality of life to citizens...

The technological ecosystem built up with the collaboration of sensors, smartphones, Cloud, Internet of Things (IoT), machine learning, deep learning, etc., functions toward societal benefit in terms of smart healthcare to world population irrespective of demography. IoT-based healthcare is getting immensely popularized because it is cost-effective...

Intelligent and smart health monitoring is prevalent nowadays with the support of advancement in Internet of Things, machine learning, and ontology-based decision support systems. As a decision support system can analyze current patient vitals based on historical data, effective data representation from different data sources into a common knowledg...

Today's computational model has been undergoing a huge paradigm shift from personalized, local processing using local processing unit (LPU) to remote processing at cloud servers located globally. Advances in sensor-based smart applications such as smart home, smart health, smart transport, smart environment monitoring, etc. are generating huge data...

The ongoing COVID-19 pandemic has caused worldwide socioeconomic unrest, forcing governments to introduce extreme measures to reduce its spread. Being able to accurately forecast the effect of unlocking in India, would allow governments to alter their policies accordingly and plan ahead. The study investigated prediction forecasts using the ARIMA m...

IoT based applications such as smart healthcare, transportation, surveillance etc. lead to more convenient and healthy lifestyle to human being nowadays. Biosensors sense health vitals and send acquired data to cloud server for processing. These huge sensory health data need to be processed and analyzed efficiently and intelligently for knowledge e...

Indoor localization systems have the capability to change the way of providing location-based services in a closed environment. Though there is no agreed-upon technology that works best in indoor, WiFi signal is an important alternative as most of such places are covered by WiFi Access Points (APs). In this paper, the problem of indoor localization...

On the lap of this modern era, human activity recognition (HAR) has been of great help in case of health monitoring and rehabilitation. Existing works mostly use one or more specific devices (with embedded sensors) including smartphones for activity recognition and most of the time the detected activities are coarse grained like sit or walk rather...

In mobile crowd-sensing, smartphone users take part in sensing and then share the data to the server (cloud) and get an incentive. These data can be utilized for providing better services to improve quality of life. Batteries used in smartphones constrain the usability of these devices for longer charge cycles. Hence, maintaining a balance between...

Computation offloading effectively expands the usability of mobile terminals beyond their physical limits, and also greatly extends their battery charging intervals. Offloading or cyber foraging is a technique by which large and complex computational jobs are relocated from lightweight portable devices (such as smartphones) called offloadee to powe...

Recommender Systems have become essential in personalized healthcare as they provide meaningful information to the patients depending on the specific requirements and availability of health records. With the improvement of machine learning techniques, the recommender system brings about several opportunities to the medical science. Systems can perf...

Today's computational model has been undergoing a huge paradigm shift from personalized, local processing using local processing unit (LPU) to remote processing at cloud servers located globally. Advances in sensor-based smart applications such as smart home, smart health, smart transport, smart environment monitoring, etc. are generating huge data...

Ambient assisted living (AAL) is focused on providing assistance to patients primarily in their natural environment to improve their quality of life. AAL domain has evolved at a fast pace as the stakeholders of AAL include patients and their relatives, social services, and care givers. AAL follows a multi-tier architecture where data from body area...

A new era of ubiquitous indoor location awareness is on the horizon especially for context sensing, ambient assisted living and many other smart city applications. Although indoor localization plays a pivotal role in making the environment smarter, it is still very difficult to compare state-of-the-art localization algorithms due to the scarcity of...

By embracing the potential of IoT and smartphones, traditional cities can be transformed to smart cities. The success of such smart city mission is firmly vested in populace and thus it should have a bottom-up nature, initiated by the citizens. This paper focuses on the design and development of a unified framework, which can provide a platform to...

The introduction of medical Internet of Things (IoT) for biomedical applications has brought about the era of proactive healthcare. Such advanced medical supervision lies on the foundation of a network of energy-constrained wearable or implantable sensors (or things). These miniaturized battery-powered biosensor nodes are placed in, on, or around t...

VehicularAdhoc Network (VANET) is one of the interesting and challenging research areas in mobile communication domain. For the past few decades, researchers are trying to develop appropriate routing protocols for VANET. Among the different types of bio-inspired algorithms, Ant Colony Optimization (ACO) is found to be most recent and efficient tech...

Human activity recognition is an important technology in pervasive computing as it provides valuable information for smart healthcare and assisted living applications. Use of smartphones for activity recognition poses new challenges due to variation in hardware configuration and usage behaviour like how the smartphone is kept. Only a few recent wor...

Human activity recognition is increasingly used for medical, surveillance and entertainment applications. For better monitoring, these applications require identification of detailed activity like sitting on chair/floor, brisk/slow walking, running, etc. This paper proposes a ubiquitous solution to detailed activity recognition through the use of s...

Sensors embedded in smart handheld can be extremely useful in providing information on people's activities and behaviors, that can be extremely useful in smart home, smart healthcare applications. Existing work mostly uses one or more specific devices (with embedded sensors) for activity recognition and most of the time the detected activities are...

Indoor localization, based on Wi-Fi signals, is becoming a popular approach for providing location based services in indoor environment. The challenging task of accurately finding the position of a device depends on prior efforts of fingerprinting. However, fingerprint data are susceptible to many indoor environmental factors such as, change of fur...

Wireless sensor networks can be deployed in remote areas for monitoring rainforest, bio-diversity, detecting forest fire or even surveillance. In such remote monitoring applications, sensor nodes are deployed in unattended environments that make them vulnerable to different kind of failures. Hence, it is extremely important to perform a reliability...

Recent advancements in Ambient Assisted Living (AAL) have produced innovative ways to address the needs of people with impairments and elderly improving their quality of life at the stage when it is most desirable. A typical AAL system consists of ubiquitous computing, sensing and communication blocks where wireless ad hoc, body area and sensor net...