Sarbani Roy

Jadavpur University | JU · Department of Computer Science and Engineering

Road surfaces can contain a lot of anomalies such as potholes. Understanding and detecting such irregularities are a key towards building a safe road transport system and a step towards building a smart city. This paper makes an attempt to classify road surface images using transfer learning on pre-trained convolution neural network (CNN) based mod...

Identification of the actual sensor data provider is important in smartphone-based participatory sensing systems. More specifically, the participatory sensing systems must be able to identify the actual users from smartphone-embedded sensors’ data in a fast, silent, and unobtrusive manner, ensuring that appropriate privacy protection and authentica...

The imposition of strict restrictions by the Government of India to restrict the spread of the novel coronavirus has changed the socio-economic landscape like never before. The air quality due to such unprecedented events has undergone drastic changes especially in major metropolitan cities, which serve as important financial and industrial hubs of...

Emotion detection is a promising field of research in multiple perspectives such as psychology, marketing, network analysis and so on. Multiple models have been suggested over the years for accurate and efficient mood detection. Identifying emotion, or mood, from text has progressed from a simple frequency distribution analysis to far more complica...

One of the most challenging tasks in time-series prediction is a model’s capability to accurately learn the repeating granular trends in the data’s structure to generate effective predictions. Traditionally specially tuned statistical models and deep learning models like recurrent neural networks and long short-term memory networks are used to tack...

With ever-increasing global air pollution levels, researchers are exploring ways to forecast air pollutant concentrations to prevent the adverse effects of air pollution on humans. Powered by the data obtained from air pollution monitoring stations, we now have a chance to build sophisticated models to estimate the future concentration of various a...

Existence of several challenges and high cost in the development of monitoring infrastructure have become major reasons for data sparsity by statutory government agencies tasked to study pollution exposure in urban areas. As an effort to mitigate this problem, the recent usage of satellite aerosol optical depth data along with the usage of learning...

Existence of several challenges and high cost in the development of monitoring infrastructure have become major reasons for data sparsity by statutory government agencies tasked to study pollution exposure in urban areas. As an effort to mitigate this problem, the recent usage of satellite aerosol optical depth data along with the usage of learning...

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...

With rising pollution concerns in recent times, producing refined and accurate predictions as a part of United Nations Sustainable Development Goals 11 (Sustainable Cities and Communities) and 13 (Climate Action) have gained utmost importance. As new computational methods become available, it becomes difficult for an average policymaker to evaluate...

In any online social media platform, it is necessary to reduce the effect of rumor data from original information as it may cause harm to society. Influential users can be detected through different centrality measures. When the rumor is generated through some influential users, they have more impact on society. Here, we have proposed a prognostic...

Analysis and prediction on real time air quality data is a critical step in solving various problems related to pollution and finding a genuine solution. However, missing values in air pollution data is a serious issue that may greatly influence the performance of such analysis and prediction. In order to address this problem, a 2-step process is p...

The behaviour of individual users in an online social network is a major contributing factor in determining the outcome of multiple network phenomenon. Group formation, growth of the network, information propagation, and rumour blocking are some of the many network behavioural traits that are influenced by the interaction patterns of the users in t...

Emotion identification based on multimodal data (e.g., audio, video, text, etc.) is one of the most demanding and important research fields, with various uses. In this context, this research work has conducted a rigorous exploration of model-level fusion to find out the optimal multimodal model for emotion recognition using audio and video modaliti...

Forecasting time series has acquired immense research importance and has vast applications in the area of air pollution monitoring. This work attempts to investigate the abilities of various existing techniques when applied for short term, high granular time series forecasting of PM2.5. More specifically, a comparative study has been provided, taki...

Occupancy detection and prediction are two well-established problems which can be improved further to achieve higher accuracy in both cases than the existing solutions. To achieve the desired higher accuracy, proposed OccupancySense model detects human presence and predicts indoor occupancy count by the fusion of Internet of Things (IoT) based indo...

Poor air quality is becoming a critical environmental concern in different countries over the last several years. Most of the air pollutants have serious consequences on human health and wellbeing. In this context, efficient forecasting of air pollutants is currently crucial to predict future events with a view to taking corrective actions and fram...

In smartphone-based crowd/participatory sensing systems, it is necessary to identify the actual sensor data provider. In this context, this paper attempts to recognize the users’ identity based on their gait patterns (i.e. unique walking patterns). More specifically, a deep convolution neural network (CNN) model is proposed for the user identificat...

As the number of enterprises dispatching their workload to the cloud has increased significantly over the last decade, service level agreements (SLAs) becoming a key element to consider for maintaining the quality of service (QoS). In order to facilitate the perseverance of service quality at a satisfactory level, clouds perform load balancing thro...

Adequate nighttime lighting of city streets is necessary for safe vehicle and pedestrian movement, deterrent of crime, improvement of the citizens’ perceptions of safety, and so on. However, monitoring and mapping of illumination levels in city streets during the nighttime is a tedious activity that is usually based on manual inspection reports. Th...

Air pollution has become a major environmental risk of the new civilized world due to its severe influence on public health and the environment. Eventually, understanding the spatiotemporal variability of air pollution at high granularity is necessary to make relevant public policies. To explore spatiotemporal variability of air pollution at high g...

Tackling air pollution has become of utmost importance since the last few decades. Different statistical as well as deep learning methods have been proposed till now, but seldom those have been used to forecast future long-term pollution trends. Forecasting long-term pollution trends into the future is highly important for government bodies around...

The demand of cloud-based services is growing rapidly due to the high scalability and cost-effective nature of cloud infrastructure. As a result, the size of the data center is increasing drastically, so is the cost of maintenance in terms of resource management and energy consumption. Hence, it is important to develop a proper resource management...

Rising real estate prices along with expensive maintenance costs, and lack of spares during times of instrument failure have become major issues for statutory bodies when dealing with real-time pollution monitoring stations. As a possible solution to these problems, a novel class of hybrid spatio-temporal pollution forecasting networks which are a...

From the popular concept of six-degree separation, social networks are generally analyzed in the perspective of small world networks where centrality of nodes play a pivotal role in information propagation. However, working with a large dataset of a scale-free network (which follows power law) may be different due to the nature of the social graph....

Proper maintenance of roads is an extremely complex task and also an important issue all over the world. One of the most critical road monitoring and maintenance activities is the detection of road anomalies such as potholes. Identification of potholes is necessary to avoid road accidents, prevent damage of vehicles, enhance travelling comforts, et...

Spatial distributions of data of natural phenomena can be estimated by using different spatial interpolation techniques. These techniques can be used for the purpose of developing urban noise pollution monitoring applications, so they can truly describe the actual urban noise pollution scenario of any region of interest to make effective and inform...

Indoor air pollutants e.g., Carbon dioxide (CO2), Particulate Matter(PM)2.5, PM10, Total Volatile Organic Compounds (TVOC), etc. have a serious impact on human health. Out of these pollutants, CO2 is one of the most dominant one. Hence, proper monitoring and control of this pollutant is an important part of maintaining a healthy indoor. To make thi...

COVID-19 is a global crisis where India is going to be one of the most heavily affected countries. The variability in the distribution of COVID-19-related health outcomes might be related to many underlying variables, including demographic, socioeconomic, or environmental pollution related factors. The global and local models can be utilized to exp...

Energy harvesting facilitates Wireless Sensor Networks (WSN) to work in perpetual mode. But, the amount and duration of green energy depend on the unpredictable behavior of ambient energy sources. Limited knowledge of future energy availability is the main con-straint in designing routing and MAC (Medium Access Control) protocol. If the prediction...

With the advancement of technology urban city dynamics are changing rapidly. Cities are becoming smart faster with different initiatives taken by the government along with private organizations. These technical upgradations are changing the life of the citizens at a fast pace. The needs of the citizens are the primary driving forces behind the city...

The governance for smart cities will be more citizen-centric and government policies will be based on the demand of the citizen. Social network has the potential of elevating the governance process to new levels. It enables government for instantaneous transmission of information to the targeted citizen, processing large scale data available throug...

Indoor Air Pollution is one of the most ignored topics that require serious investigation. People spend most of their lives in either closed AC offices or within AC bedrooms which are not monitored at all. Several indoor air pollutants can affect human health out of which CO2 is most dominant. Time series forecasting is a very powerful tool which h...

Unified IoT framework is an absolute necessity when IoT is revolutionizing the Industry. In this Industry 4.0 revolution, IoT is playing a key role in the development process. Any present-day real-world application will end with a smart solution when integrated IoT . A large variety of real-world applications maintaining different standards are alr...

Currently, all online social networks (OSNs) are considered to follow a power-law distribution. In this paper, the degree distribution for multiple OSNs has been studied. It is seen that the degree distributions of OSNs differ moderately from a power law. Lognormal distributions are an alternative to power-law distributions and have been used as be...

COVID-19 is a global crisis where India is going to be one of the most heavily affected countries. The variability in the distribution of COVID-19-related health outcomes might be related to many underlying variables, including demographic, socioeconomic, or environmental pollution related factors. The global and local models can be utilized to exp...

Participatory sensing has become an effective way of sensing urban dynamics due to the widespread availability of smartphones among citizens. Traditionally, separate urban sensing applications are designed to monitor different urban dynamics like environment, transportation, mobility, etc. However, combining these applications to aggregate informat...

Indoor Air Quality (IAQ) Forecasting using Time Series Forecasting Methods

The technology, cloud computing, in present days, is vastly used due to the services it provides and the ease with which they can be availed. The enormous development of the Internet technology is due to the advent of the concept of cloud. Along with its benefits, cloud computing brings along itself a detrimental side effect, i.e., carbon emission....

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...

Changes in the BAN topology are caused due to the body movement induced by repeated activities like walking, running, twisting, turning and waving arms. In such activities, individual nodes may move relative to each other and along with this, the entire BAN may move its absolute location, which can induce several complexities in the network like re...

Cloud federation is a new computing paradigm that has paved the way for cloud service providers (CSPs) to offer their unused resources (virtual machine) to other CSPs when their resource demands are low. Federation also allows CSPs to outsource their resource requests to other CSPs when their computing resources' demands are high. Thus, in cloud fe...

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...

Online Social Networks (OSNs) are largely popular. People interact daily on networks such as Facebook, Twitter, YouTube, Email, Messenger, WhatsApp, Google+, Quora, LiveJournal etc. and the types of interaction on these networks are different. The types of content that people share on these networks are also different. Each of the OSNs serves a dif...

The growing market of cloud computing resulted in increased demand for cloud resources and it will become difficult for individual service providers (SPs) to fulfill all resource requests. That leads to a situation where two or more SPs may form a group and share the resources. Now, due to the formation of more than one federations by different clo...

Information propagation in the network is probabilistic in nature; simultaneously, it depends on the connecting paths of the propagation. Selection of seed nodes plays an important role in determining the levels and depth of the contagion in the network. This paper presents a comparative study when seed nodes for information propagation are selecte...

The application of wireless sensor networks (WSNs) technology in monitoring systems is demanding more efficient services to fulfill the requirements of the monitoring task. For this purpose, the simultaneous presence of features such as different communication mediums (air and water) used by nodes and various sizes of data generated by heterogeneou...

The emergence of cloud computing has led to an astronomical growth in the computing services provided by vendors over the cloud interface. This has led to the paradigm of cloud federations where a group of CSPs collaborate to form a federation for seamless provisioning of resource requests. In this paper, cloud federation formation framework is mod...

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...

Cloud federation has paved the way for cloud service providers (CSP) to collaborate with other CSPs to serve users’ resource requests, which are prohibitively high for any single CSP during peak time. Moreover, to entice different CSPs to participate in federation, it is necessary to maximize the profit of all CSPs involved in the federation. Furth...

Noise pollution in urban areas is a subject of grave concern and it is being recognized globally in different countries and cities. People are facing many health-related problems because of this. Therefore, in the proposed work, we envisioned to tackle the challenge of acquiring real time and spatially fine-grained noise pollution data with a commu...

With more awareness and growth in the cloud market, demands for computational resources have increased in order to provide services to the cloud users. Sometimes it is difficult for an individual cloud service provider (CSP) to meet the level of promised quality of service (QoS) and to fulfill all types of resource requests dynamically. Cloud feder...

Cloud federation has become a consolidated paradigm in which set of cooperative service providers share their unused computing resources with other members of the federation to gain some extra revenue. Due to increase in consciousness about cloud computing, demand for cloud services among cloud users have increased, thus making it hard for any sing...

GPS is one of the most used services in any location based app in our smartphone and almost a quarter of all Android apps available in the Google play store are using this GPS. But the problem is that it is costly in terms of power consumption as our smartphones are resource constrained. To resolve this, we have introduced an energy efficient conte...