Ankush Manocha

Lovely Professional University | LPU · Discipline of Computer Science

Monitoring a specific area to analyze a continuous change has become more accessible by using optical images in remote sensing technology. However, several natural and artificial aspects such as fog and air pollution make it difficult to extract correct geometric information. To overcome the limitation of optical images, Synthetic Aperture Radar (S...

As water is considered one of the essential assets of nature, the recognition of the availability of water at a specific location can help government bodies to take necessary action toward water conservation. Monitoring water from satellite images is considered one of the most difficult areas of pattern recognition. In this manner, a novel multi-le...

Recent advancements in remote sensing technologies, as well as high-resolution satellite images, have opened up new avenues for comprehending the earth's surfaces. However, owing to the significant unpredictability in satellite data, satellite images categorization is a difficult task. Availability of the satellite dataset is a challenging task in...

Since the development of smart healthcare services, different solutions have been developed in the field of healthcare to increase the life expectancy of the patient by reducing the cost of healthcare. Digital Twin (DT) is considered one of the most promising technologies and a game changer in the field of healthcare. DT is generating a virtual imi...

A recent study has successfully focused on Deep Learning and Blockchain technologies because of their tremendous potential for producing reliable decisions. The bulk of contemporary deep learning techniques implemented on centralized servers gives operational transparency, traceability, reliability, security, and reliable data provenance qualities....

Recently, Deep Learning and blockchain technology has gained successful attention in recent research due to their high potential for generating accurate decision. The operational transparency, traceability, dependability, security, and trustworthy data provenance characteristics are offered by the vast majority of current deep learning approaches t...

A recent study has successfully focused on Deep Learning and Blockchain technologies because of their tremendous potential for producing reliable decisions. The bulk of contemporary deep learning techniques implemented on centralized servers gives operational transparency, traceability, reliability, security, and reliable data provenance qualities....

Panic disorder (PD) is considered one of the destructive ailments, with various individuals experiencing a critical functional disorder. As the range of remission for PD is achieved only between 20% and 50% with the help of regular pharmacotherapy, modern solutions are expected to deal with this issue. By taking the advantage of the Internet of Thi...

Over the last two years, the novel coronavirus has become a significant threat to the health of the public, and numerous approaches are developed to determine the symptoms of COVID-19. To deal with the complex symptoms of COVID-19, a Deep Learning-assisted Multi-modal Data Analysis (DMDA) approach is introduced to determine COVID-19 symptoms by uti...

Diarrhea is one of the most common infectious diseases that affect people of all ages and is a serious public health concern around the world. The main causes of diarrhea include food quality, water, indoor meteorological, and outdoor meteorological conditions. In this study, a dew computing-assisted smart monitoring framework is developed to evalu...

Flooding and other natural disasters may have a devastating impact on property and human life. We need a precise flooding evaluation of the impacted region after the occurrence to avail rescuing through a crisis reaction unit. Obtaining an accurate estimate of a flooded region traditionally requires a huge amount of human resources. To overcome thi...

The present invention relates to a system (100) of remote monitoring and control of automotive air conditioning and heating system. The smart system (100) includes a temperature sensor module (102), a central controller (101), a low power wireless personal area network (111) and a customized mobile app (112). The smart system (100) after being acti...

Current advancement in Internet-of-Things, Cyber-Physical Systems, Cloud-of-Things, and Edge-of-Things technologies have enabled us to design more advanced and event-sensitive real-time monitoring solutions. IoT-assisted healthcare systems need local data processing environment for effective decision making. In the proposed study, a novel edge anal...

COVID-19 is a life-threatening contagious virus that has spread across the globe rapidly. To reduce the outbreak impact of COVID-19 virus illness, continual identification and remote surveillance of patients are essential. Medical service delivery based on the Internet of Things (IoT) technology backed up by the fog-cloud paradigm is an efficient a...

Agribusiness is directly dependent on the precise monitoring of paddy areas to take considerable supportive actions towards food security. For this, satellite-based data is considered one of the effective solutions. In this manner, the goal of this study is to design an intelligent framework to determine the crop area by using satellite data that i...

Indoor environment pollution is one of the significant concerns related to the individual's health of every category. As a majority of the population is spending their time indoors, the research on environment monitoring is realized on priority. In this research, the correlation between the indoor environment and health is determined to predict the...

This invention relates to Disclosing herewith a System of Automatic annotation of multi-spectral high-resolution satellite images Using Deep Learning The approach comprises a convolutional Neural Network (CNN) (102), CRF- FCN (104), and Bi-Directional Gated Recurrent Unit (Bi-GRU) (105).

In this pandemic, providing a quality environment is considered one of the essential objectives of smart wellbeing observation. Therefore, the prediction of irregular events has become a fundamental requirement of assistive or clinical consideration. By concentrating on this need, a dew computation-inspired irregular physical event determination so...

Waterbody identification from satellite images in an automated manner is one of the difficult tasks in the domain of Remote Sensing (RS). In recent years, several image processing approaches have been developed to process RGB or multispectral images to analyze the availability of land, water prediction, object detection, climate change, LULC, and m...

In the context of climate change, the extraction of accurate information on natural resources becomes necessary and is considered one of the most challenging tasks in the field of remote sensing. The identification of water resources has achieved considerable attention in the field of remote sensing to deal with the problem of water scarcity. In th...

Sedentary behavior is very common in today’s lifestyle that causes several metabolic and cardiovascular diseases. The high scale of physical inactiveness with inadequate activities such as drinking alcohol, smoking and negligence of healthy diet causes extreme health issues. Therefore, it becomes essential to recognize health, behavioral, and envir...

Physical activity recognition has become one of the prominent domain of research in the field of smart healthcare. The identification of physical activities through wearable sensors provide significant information about the functional ability and lifestyle of an individual. In this article, a smart physical activity-assisted behavior prediction fra...

Satellite images taken on the earth's surface are analyzed to identify the spatial and temporal changes that have occurred naturally or manmade. Real-time prediction of change provides an understanding related to the land cover, environmental changes, habitat fragmentation, coastal alteration, urban sprawl, etc. In the current study, various digita...

Bronchial asthma is one of the most common chronic diseases of childhood and considered as a major health problem globally. The irregularity in meteorological factors has become a primary cause of health severity for the individuals suffering from asthma. In the presented research, a dew-cloud assisted cyber-physical system (CPS) is proposed to ana...

Satisfying the expectations of quality living is essential for smart healthcare. Therefore, the determination of health afflictions in real-time has been considered as one of the most necessary parts of medical or assistive-care domain. In this article, a novel fog analytic-assisted deep learning-enabled physical stance-based irregularity recogniti...

Domestic veterinary care is contemplated as one of the significant domains of the healthcare industry. Conspicuously, this research presents a Smart Home-based healthcare monitoring framework for domesticated animals in real-time. The research work employs the Internet of Things (IoT)-based data acquisition in the ambient environment of the home. A...

Information and Communication Technology (ICT) empowered by the Internet of Things (IoT), and fog-cloud paradigm has been widely adopted in several domains of logistics, healthcare, and agriculture. Inspired by the enormous benefits of IoT technology, this research proposes a novel notion of smart restaurants for assessing the food quality using ga...

Sleep deprivation is one of the most underdiagnosed ailments in patients with spinal cord injuries, causing anxiety and leading to physical and mental imbalance. To address this issue, we propose a fog-assisted smart monitoring framework to detect patients' health and environmental conditions in real time.

Generalized Anxiety Disorder (GAD) is a psychological disorder caused by high stress from daily life activities. It causes severe health issues, such as sore muscles, low concentration, fatigue, and sleep deprivation. The less availability of predictive solutions specifically for individuals suffering from GAD can become an imperative reason for he...

Ever advancing development in Computer Vision and Deep Learning has increased the efficacy of smart monitoring by analyzing and predicting the physical abnormalities and generating time-sensitive results. Based on the improved principles of smart monitoring and data processing, a novel computer vision assisted deep learning based posture monitoring...

Autism Spectrum Disorder (ASD) is distinguished by a variety of behavioral and social deficits. One of the most prominent problems in an autistic child is their aggressive nature that can cause physical injuries. In order to address the following behavioral deficits, this paper is an attempt to present a novel monitoring framework to predict irregu...