Search results for: Hyperspectral remote sensing

Authors: Gabrielle Peck, Ryan Hayes

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This research presents the design and creation of a drone gas analyser, aimed at addressing the need for independent data collection and analysis of gas emissions during large-scale fires, particularly wasteland fires. The analyser drone, comprising a lightweight gas analysis system attached to a remote-controlled drone, enables the real-time assessment of smoke toxicity and the monitoring of gases released into the atmosphere during such incidents. The key components of the analyser unit included two gas line inlets connected to glass wool filters, a pump with regulated flow controlled by a mass flow controller, and electrochemical cells for detecting nitrogen oxides, hydrogen cyanide, and oxygen levels. Additionally, a non-dispersive infrared (NDIR) analyser is employed to monitor carbon monoxide (CO), carbon dioxide (CO₂), and hydrocarbon concentrations. Thermocouples can be attached to the analyser to monitor temperature, as well as McCaffrey probes combined with pressure transducers to monitor air velocity and wind direction. These additions allow for monitoring of the large fire and can be used for predictions of fire spread. The innovative system not only provides crucial data for assessing smoke toxicity but also contributes to fire prediction and management. The remote-controlled drone's mobility allows for safe and efficient data collection in proximity to the fire source, reducing the need for human exposure to hazardous conditions. The data obtained from the gas analyser unit facilitates informed decision-making by emergency responders, aiding in the protection of both human health and the environment. This abstract highlights the successful development of a drone gas analyser, illustrating its potential for enhancing smoke toxicity analysis and fire prediction capabilities. The integration of this technology into fire management strategies offers a promising solution for addressing the challenges associated with wildfires and other large-scale fire incidents. The project's methodology and results contribute to the growing body of knowledge in the field of environmental monitoring and safety, emphasizing the practical utility of drones for critical applications.

Keywords: fire prediction, drone, smoke toxicity, analyser, fire management

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Authors: Anupam Bhatia

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Upon reviewing the literature and the pragmatic work done in the field of E- textiles, it is observed that the applications of wearable technologies have found a steady growth in the field of military, medical, industrial, sports; whereas fashion is at a loss to know how to treat this technology and bring it to market. The purpose of this paper is to understand the practical issues of integration of electronics in garments; cutting patterns for mass production, maintaining the basic properties of textiles and daily maintenance of garments that hinder the wide adoption of interactive fabric technology within Fashion and leisure wear. To understand the practical hindrances an experimental and laboratory approach is taken. “Techno Meets Fashion” has been an interactive fashion project where sensor technologies have been embedded with textiles that result in set of ensembles that are light emitting garments, sound sensing garments, proximity garments, shape memory garments etc. Smart textiles, especially in the form of textile interfaces, are drastically underused in fashion and other lifestyle product design. Clothing and some other textile products must be washable, which subjects to the interactive elements to water and chemical immersion, physical stress, and extreme temperature. The current state of the art tends to be too fragile for this treatment. The process for mass producing traditional textiles becomes difficult in interactive textiles. As cutting patterns from larger rolls of cloth and sewing them together to make garments breaks and reforms electronic connections in an uncontrolled manner. Because of this, interactive fabric elements are integrated by hand into textiles produced by standard methods. The Arduino has surely made embedding electronics into textiles much easier than before; even then electronics are not integral to the daily wear garments. Soft and flexible interfaces of MEMS (micro sensors and Micro actuators) can be an option to make this possible by blending electronics within E-textiles in a way that’s seamless and still retains functions of the circuits as well as the garment. Smart clothes, which offer simultaneously a challenging design and utility value, can be only mass produced if the demands of the body are taken care of i.e. protection, anthropometry, ergonomics of human movement, thermo- physiological regulation.

Keywords: ambient intelligence, proximity sensors, shape memory materials, sound sensing garments, wearable technology

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Authors: Rania Raouf Sedky

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Adaptive architecture relates to buildings specifically designed to adapt to their residents and their environments. To design a biologically adaptive system, we can observe how living creatures in nature constantly adapt to different external and internal stimuli to be a great inspiration. The issue is not just how to create a system that is capable of change but also how to find the quality of change and determine the incentive to adapt. The research examines the possibilities of transforming spaces using the human body as an active tool. The research also aims to design and build an effective dynamic structural system that can be applied on an architectural scale and integrate them all into the creation of a new adaptive system that allows us to conceive a new way to design, build and experience architecture in a dynamic manner. The main objective was to address the possibility of a reciprocal transformation between the user and the architectural element so that the architecture can adapt to the user, as the user adapts to architecture. The motivation is the desire to deal with the psychological benefits of an environment that can respond and thus empathize with human emotions through its ability to adapt to the user. Adaptive affiliations of kinematic structures have been discussed in architectural research for more than a decade, and these issues have proven their effectiveness in developing kinematic structures, responsive and adaptive, and their contribution to 'smart architecture'. A wide range of strategies have been used in building complex kinetic and robotic systems mechanisms to achieve convertibility and adaptability in engineering and architecture. One of the main contributions of this research is to explore how the physical environment can change its shape to accommodate different spatial displays based on the movement of the user’s body. The main focus is on the relationship between materials, shape, and interactive control systems. The intention is to develop a scenario where the user can move, and the structure interacts without any physical contact. The soft form of shifting language and interaction control technology will provide new possibilities for enriching human-environmental interactions. How can we imagine a space in which to construct and understand its users through physical gestures, visual expressions, and response accordingly? How can we imagine a space whose interaction depends not only on preprogrammed operations but on real-time feedback from its users? The research also raises some important questions for the future. What would be the appropriate structure to show physical interaction with the dynamic world? This study concludes with a strong belief in the future of responsive motor structures. We imagine that they are developing the current structure and that they will radically change the way spaces are tested. These structures have obvious advantages in terms of energy performance and the ability to adapt to the needs of users. The research highlights the interface between remote sensing and a responsive environment to explore the possibility of an interactive architecture that adapts to and responds to user movements. This study ends with a strong belief in the future of responsive motor structures. We envision that it will improve the current structure and that it will bring a fundamental change to the way in which spaces are tested.

Keywords: adaptive architecture, interactive architecture, responsive architecture, tensegrity

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Authors: Rohit Dey, Sailendra Karra

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This paper aims at solving the problem of multi-target searching in a Global Positioning System (GPS) denied environment using swarm robots with limited sensing and communication abilities. Typically, existing swarm-based search algorithms rely on the presence of a global coordinate system (vis-à-vis, GPS) that is shared by the entire swarm which, in turn, limits its application in a real-world scenario. This can be attributed to the fact that robots in a swarm need to share information among themselves regarding their location and signal from targets to decide their future course of action but this information is only meaningful when they all share the same coordinate frame. The paper addresses this very issue by eliminating any dependency of a search algorithm on the need of a predetermined global coordinate frame by the unification of the relative coordinate of individual robots when within the communication range, therefore, making the system more robust in real scenarios. Our algorithm assumes that all the robots in the swarm are equipped with range and bearing sensors and have limited sensing range and communication abilities. Initially, every robot maintains their relative coordinate frame and follow Levy walk random exploration until they come in range with other robots. When two or more robots are within communication range, they share sensor information and their location w.r.t. their coordinate frames based on which we unify their coordinate frames. Now they can share information about the areas that were already explored, information about the surroundings, and target signal from their location to make decisions about their future movement based on the search algorithm. During the process of exploration, there can be several small groups of robots having their own coordinate systems but eventually, it is expected for all the robots to be under one global coordinate frame where they can communicate information on the exploration area following swarm search techniques. Using the proposed method, swarm-based search algorithms can work in a real-world scenario without GPS and any initial information about the size and shape of the environment. Initial simulation results show that running our modified-Particle Swarm Optimization (PSO) without global information we can still achieve the desired results that are comparable to basic PSO working with GPS. In the full paper, we plan on doing the comparison study between different strategies to unify the coordinate system and to implement them on other bio-inspired algorithms, to work in GPS denied environment.

Keywords: bio-inspired search algorithms, decentralized control, GPS denied environment, swarm robotics, target searching, unifying coordinate systems

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Authors: Ishtiaq Wahid, Masood Ahmad, Nighat Ayub, Sajad Ali

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Lifetime of a wireless sensor network (WSN) is directly proportional to the energy consumption of its constituent nodes. Routing in wireless sensor network is very challenging due its inherit characteristics. In hierarchal routing the sensor filed is divided into clusters. The cluster-heads are selected from each cluster, which forms a hierarchy of nodes. The cluster-heads are used to transmit the data to the base station while other nodes perform the sensing task. In this way the lifetime of the network is increased. In this paper a comparative study of hierarchal routing protocols are conducted. The simulation is done in NS-2 for validation.

Keywords: WSN, cluster, routing, sensor networks

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Authors: Jaya Mathew

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Many organizations are faced with the challenge of how to analyze and build Machine Learning models using their sensitive telemetry data. In this paper, we discuss how users can leverage the power of R without having to move their big data around as well as a cloud based solution for organizations willing to host their data in the cloud. By using ScaleR technology to benefit from parallelization and remote computing or R Services on premise or in the cloud, users can leverage the power of R at scale without having to move their data around.

Keywords: predictive maintenance, machine learning, big data, cloud based, on premise solution, R

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Authors: Rekioua D., Mohammedi A., Rekioua T., Mehleb Z.

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Photovoltaic water pumping systems is considered as one of the most promising areas in photovoltaic applications, the economy and reliability of solar electric power made it an excellent choice for remote water pumping. Two conventional techniques are currently in use; the first is the directly coupled technique and the second is the battery buffered photovoltaic pumping system. In this paper, we present different performances of a three operation modes of photovoltaic pumping system. The aim of this work is to determine the effect of different parameters influencing the photovoltaic pumping system performances, such as pumping head, System configuration and climatic conditions. The obtained results are presented and discussed.

Keywords: batteries charge mode, photovoltaic pumping system, pumping head, submersible pump

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Authors: Dan Kanmegne

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Africa will become the most populated continent by the end of the century, with around 4 billion inhabitants. Food security and climate changes will become continental issues since agricultural practices depend on climate but also contribute to global emissions and land degradation. Agroforestry has been identified as a cost-efficient and reliable strategy to address these two issues. It is defined as the integrated management of trees and crops/animals in the same land unit. Agroforestry provides benefits in terms of goods (fruits, medicine, wood, etc.) and services (windbreaks, fertility, etc.), and is acknowledged to have a great potential for carbon sequestration; therefore it can be integrated into reduction mechanisms of carbon emissions. Particularly in sub-Saharan Africa, the constraint stands in the lack of information about both areas under agroforestry and the characterization (composition, structure, and management) of each agroforestry system at the country level. This study describes and quantifies “what is where?”, earliest to the quantification of carbon stock in different systems. Remote sensing (RS) is the most efficient approach to map such a dynamic technology as agroforestry since it gives relatively adequate and consistent information over a large area at nearly no cost. RS data fulfill the good practice guidelines of the Intergovernmental Panel On Climate Change (IPCC) that is to be used in carbon estimation. Satellite data are getting more and more accessible, and the archives are growing exponentially. To retrieve useful information to support decision-making out of this large amount of data, satellite data needs to be organized so to ensure fast processing, quick accessibility, and ease of use. A new solution is a data cube, which can be understood as a multi-dimensional stack (space, time, data type) of spatially aligned pixels and used for efficient access and analysis. A data cube for Burkina Faso has been set up from the cooperation project between the international service provider WASCAL and Germany, which provides an accessible exploitation architecture of multi-temporal satellite data. The aim of this study is to map and characterize agroforestry systems using the Burkina Faso earth observation data cube. The approach in its initial stage is based on an unsupervised image classification of a normalized difference vegetation index (NDVI) time series from 2010 to 2018, to stratify the country based on the vegetation. Fifteen strata were identified, and four samples per location were randomly assigned to define the sampling units. For safety reasons, the northern part will not be part of the fieldwork. A total of 52 locations will be visited by the end of the dry season in February-March 2020. The field campaigns will consist of identifying and describing different agroforestry systems and qualitative interviews. A multi-temporal supervised image classification will be done with a random forest algorithm, and the field data will be used for both training the algorithm and accuracy assessment. The expected outputs are (i) map(s) of agroforestry dynamics, (ii) characteristics of different systems (main species, management, area, etc.); (iii) assessment report of Burkina Faso data cube.

Keywords: agroforestry systems, Burkina Faso, earth observation data cube, multi-temporal image classification

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Authors: Govinda Pathak

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In modern agriculture, the sustainable enhancement of crop productivity while minimizing environmental impacts remains a paramount challenge. Plant Growth Promoting Rhizobacteria (PGPR) have emerged as a promising solution to address this challenge. The rhizosphere, the dynamic interface between plant roots and soil, hosts intricate microbial interactions crucial for plant health and nutrient acquisition. PGPR, a subset of rhizospheric microorganisms, exhibit multifaceted beneficial effects on plants. Their abilities to stimulate growth, confer stress tolerance, enhance nutrient availability, and suppress pathogens make them invaluable contributors to sustainable agriculture. This work examines the pivotal role of free living nitrogen fixer in optimizing agricultural practices. We delve into the intricate mechanisms underlying PGPR-mediated plant-microbe interactions, encompassing quorum sensing, root exudate modulation, and signaling molecule exchange. Furthermore, we explore the diverse strategies employed by PGPR to enhance plant resilience against abiotic stresses such as drought, salinity, and metal toxicity. Additionally, we highlight the role of PGPR in augmenting nutrient acquisition and soil fertility through mechanisms such as nitrogen fixation, phosphorus solubilization, and mineral mobilization. Furthermore, we discuss the potential of PGPR in minimizing the reliance on chemical fertilizers and pesticides, thereby contributing to environmentally friendly agriculture. However, harnessing the full potential of PGPR requires a comprehensive understanding of their interactions with host plants and the surrounding microbial community. We also address challenges associated with PGPR application, including formulation, compatibility, and field efficacy. As the quest for sustainable agriculture intensifies, harnessing the remarkable attributes of PGPR offers a holistic approach to propel agricultural productivity while maintaining ecological balance. This work underscores the promising prospect of free living nitrogen fixer as a panacea for addressing critical agricultural challenges regarding chemical urea in an era of sustainable and resilient food production.

Keywords: PGPR, nitrogen fixer, quorum sensing, Rhizobacteria, pesticides

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Authors: Dominique Arrouays, Songchao Chen, Anne C. Richer-De-Forges

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Soils are at the crossing of many issues such as food and water security, sustainable energy, climate change mitigation and adaptation, biodiversity protection, human health and well-being. They deliver many ecosystem services that are essential to life on Earth. Therefore, there is a growing demand for soil information on a national and global scale. Unfortunately, many countries do not have detailed soil maps, and, when existing, these maps are generally based on more or less complex and often non-harmonized soil classifications. An estimate of their uncertainty is also often missing. Thus, there are not easy to understand and often not properly used by end-users. Therefore, there is an urgent need to provide end-users with spatially exhaustive grids of essential soil properties, together with an estimate of their uncertainty. One way to achieve this is digital soil mapping (DSM). The concept of DSM relies on the hypothesis that soils and their properties are not randomly distributed, but that they depend on the main soil-forming factors that are climate, organisms, relief, parent material, time (age), and position in space. All these forming factors can be approximated using several exhaustive spatial products such as climatic grids, remote sensing products or vegetation maps, digital elevation models, geological or lithological maps, spatial coordinates of soil information, etc. Thus, DSM generally relies on models calibrated with existing observed soil data (point observations or maps) and so-called “ancillary co-variates” that come from other available spatial products. Then the model is generalized on grids where soil parameters are unknown in order to predict them, and the prediction performances are validated using various methods. With the growing demand for soil information at a national and global scale and the increase of available spatial co-variates national and continental DSM initiatives are continuously increasing. This short review illustrates the main national and continental advances in Europe, the diversity of the approaches and the databases that are used, the validation techniques and the main scientific and other issues. Examples from several countries illustrate the variety of products that were delivered during the last ten years. The scientific production on this topic is continuously increasing and new models and approaches are developed at an incredible speed. Most of the digital soil mapping (DSM) products rely mainly on machine learning (ML) prediction models and/or the use or pedotransfer functions (PTF) in which calibration data come from soil analyses performed in labs or for existing conventional maps. However, some scientific issues remain to be solved and also political and legal ones related, for instance, to data sharing and to different laws in different countries. Other issues related to communication to end-users and education, especially on the use of uncertainty. Overall, the progress is very important and the willingness of institutes and countries to join their efforts is increasing. Harmonization issues are still remaining, mainly due to differences in classifications or in laboratory standards between countries. However numerous initiatives are ongoing at the EU level and also at the global level. All these progress are scientifically stimulating and also promissing to provide tools to improve and monitor soil quality in countries, EU and at the global level.

Keywords: digital soil mapping, global soil mapping, national and European initiatives, global soil mapping products, mini-review

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Authors: Gagandeep Singh

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The sensor field optimization is a serious issue in WSNs and has been ignored by many researchers. As in numerous real-time sensing fields the sensor nodes on the corners i.e. on the segment boundaries will become lifeless early because no extraordinary safety is presented for them. Accordingly, in this research work the central objective is on the segment based optimization by separating the sensor field between advance and normal segments. The inspiration at the back this sensor field optimization is to extend the time spam when the first sensor node dies. For the reason that in normal sensor nodes which were exist on the borders may become lifeless early because the space among them and the base station is more so they consume more power so at last will become lifeless soon.

Keywords: WSNs, ECRSEP, SEP, field optimization, energy

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Authors: Sehreen Moorat, Hiba, Maham Mahnoor, Faryal Soomro

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Leakage of gases in a system makes infrastructures and users vulnerable; it can occur due to its environmental conditions or old groundwork. In hospitals and industries, it is very important to detect any small level of gas leakage because of their sensitivity. In this research, a portable detection system for the small leakage of gases has been developed, gas sensor (MQ-2) is used to find leakage when it’s at its initial phase. The sensor and transmitting module senses the change in level of gas by using a sensing circuit. When a concentration of gas reach at a specified threshold level, it will activate an alarm and send the alarming situation notification to receiver through GSM module. The proposed system works well in hospitals, home, and industries.

Keywords: gases, detection, Arduino, MQ-2, alarm

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Authors: Shreyansh Adesara, Sneha Pandiya

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The mobile ad-hoc network (MANET) is an important and open area research for the examination and determination of the performance evolution. Temporary ordered routing algorithm (TORA) is adaptable and distributed MANET routing algorithm which is totally dependent on internet MANET Encapsulation protocol (IMEP) for the detection of the link and sensing of the link. If IMEP detect the wrong link failure then the network suffer from congestion and unnecessary route maintenance. Thus, the improvement in link detection method of TORA is introduced by various methods on IMEP by different perspective from different person. There are also different reactive routing protocols like AODV, TORA and DSR has been compared for the knowledge of the routing scenario for different parameter and using different model.

Keywords: IMEP, mobile ad-hoc network, protocol, TORA

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Authors: Monique M. Keller, Roline Barnes, Corlia Brandt

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Introduction Scientific evidence on the hand forces and the types of grasps measurement during daily tasks are lacking, leaving a gap in the field of hand rehabilitation and robotics. Measuring the grasp forces and types produced by the individual fingers during daily functional tasks is valuable to inform and grade rehabilitation practices for second to fifth metacarpal fractures with robust scientific evidence. Feix et al, 2016 identified the most extensive and complete grasp study that resulted in the GRASP taxonomy. Covid-19 virus changed data collection across the globe and safety precautions in research are essential to ensure the health of participants and researchers. Methodology A cross-sectional study investigated six healthy adults aged 20 to 59 years, pilot participants’ hand forces during 105 tasks. The tasks were categorized into five sections namely, personal care, transport and moving around, home environment and inside, gardening and outside, and office. The predominant grasp of each task was identified guided by the GRASP Taxonomy. Grasp forces were measured with 13mm force-sensing resistors glued onto a glove attached to each of the dominant and non-dominant hand’s individual fingers. Testing equipment included Flexiforce 13millimetres FSR .5" circle, calibrated prior to testing, 10k 1/4w resistors, Arduino pro mini 5.0v – compatible, Esp-01-kit, Arduino uno r3 – compatible board, USB ab cable - 1m, Ftdi ft232 mini USB to serial, Sil 40 inline connectors, ribbon cable combo male header pins, female to female, male to female, two gloves, glue to attach the FSR to glove, Arduino software programme downloaded on a laptop. Grip strength measurements with Jamar dynamometer prior to testing and after every 25 daily tasks were taken to will avoid fatigue and ensure reliability in testing. Covid-19 precautions included wearing face masks at all times, screening questionnaires, temperatures taken, wearing surgical gloves before putting on the testing gloves 1.5 metres long wires attaching the FSR to the Arduino to maintain social distance. Findings Predominant grasps observed during 105 tasks included, adducted thumb (17), lateral tripod (10), prismatic three fingers (12), small diameter (9), prismatic two fingers (9), medium wrap (7), fixed hook (5), sphere four fingers (4), palmar (4), parallel extension (4), index finger extension (3), distal (3), power sphere (2), tripod (2), quadpod (2), prismatic four fingers (2), lateral (2), large-diameter (2), ventral (2), precision sphere (1), palmar pinch (1), light tool (1), inferior pincher (1), and writing tripod (1). Range of forces applied per category, personal care (1-25N), transport and moving around (1-9 N), home environment and inside (1-41N), gardening and outside (1-26.5N), and office (1-20N). Conclusion Scientifically measurements of finger forces with careful consideration to types of grasps used in daily tasks should guide rehabilitation practices and robotic design to ensure a return to the full participation of the individual into the community.

Keywords: activities of daily living (ADL), Covid-19, force-sensing resistors, grasps, hand forces

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Authors: V. V. Fomin, A. P. Mikhailovich, E. M. Agapitov, V. E. Rogachev, E. A. Kostousova, E. S. Perekhodova

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Ground-level landscape photos can be used as a source of objective data on woody vegetation and vegetation dynamics. We proposed a method for processing, analyzing, and presenting ground photographs, which has the following advantages: 1) researcher has to form holistic representation of the study area in form of a set of interlapping ground-level landscape photographs; 2) it is necessary to define or obtain characteristics of the landscape, objects, and phenomena present on the photographs; 3) it is necessary to create new or supplement existing textual descriptions and annotations for the ground-level landscape photographs; 4) single or multiple ground-level landscape photographs can be used to develop specialized geoinformation layers, schematic maps or thematic maps; 5) it is necessary to determine quantitative data that describes both images as a whole, and displayed objects and phenomena, using algorithms for automated image analysis. It is suggested to match each photo with a polygonal geoinformation layer, which is a sector consisting of areas corresponding with parts of the landscape visible in the photos. Calculation of visibility areas is performed in a geoinformation system within a sector using a digital model of a study area relief and visibility analysis functions. Superposition of the visibility sectors corresponding with various camera viewpoints allows matching landscape photos with each other to create a complete and wholesome representation of the space in question. It is suggested to user-defined data or phenomenons on the images with the following superposition over the visibility sector in the form of map symbols. The technology of geoinformation layers’ spatial superposition over the visibility sector creates opportunities for image geotagging using quantitative data obtained from raster or vector layers within the sector with the ability to generate annotations in natural language. The proposed method has proven itself well for relatively open and clearly visible areas with well-defined relief, for example, in mountainous areas in the treeline ecotone. When the polygonal layers of visibility sectors for a large number of different points of photography are topologically superimposed, a layer of visibility of sections of the entire study area is formed, which is displayed in the photographs. Also, as a result of this overlapping of sectors, areas that did not appear in the photo will be assessed as gaps. According to the results of this procedure, it becomes possible to obtain information about the photos that display a specific area and from which points of photography it is visible. This information may be obtained either as a query on the map or as a query for the attribute table of the layer. The method was tested using repeated photos taken from forty camera viewpoints located on Ray-Iz mountain massif (Polar Urals, Russia) from 1960 until 2023. It has been successfully used in combination with other ground-based and remote sensing methods of studying the climate-driven dynamics of woody vegetation in the Polar Urals. Acknowledgment: This research was collaboratively funded by the Russian Ministry for Science and Education project No. FEUG-2023-0002 (image representation) and Russian Science Foundation project No. 24-24-00235 (automated textual description).

Keywords: woody, vegetation, repeated, photographs

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Authors: Samra Naz, Aneeqa Ahmed, Qurat-ul-ain Mubarak, Irum Nausheen

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Driver safety systems protect driver from accidents by sensing signs of drowsiness. The paper proposes a technique which can detect the signs of drowsiness and make corresponding decisions to make the driver alert. This paper presents a technique in which the driver will be continuously monitored by a camera and his eyes, head and mouth movements will be observed. If the drowsiness signs are detected on the basis of these three movements under the predefined criteria, driver will be declared as sleepy and he will get alert with the help of alarms. Three robust techniques of drowsiness detection are combined together to make a robust system that can prevent form accident.

Keywords: drowsiness, eye closure, fatigue detection, yawn detection

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Authors: Ivanka Valova

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This paper is aimed at using a multi-agent approach to monitor and diagnose a biotechnological system in order to validate certain control actions depending on the process development and the operating conditions. A multi-agent system is defined as a network of interacting software modules that collectively solve complex tasks. Remote monitoring and control of biotechnological processes is a necessity when automated and reliable systems operating with no interruption of certain activities are required. The advantage of our approach is in its flexibility, modularity and the possibility of improving by acquiring functionalities through the integration of artificial intelligence.

Keywords: multi-agent approach, artificial intelligence, biotechnological processes, anaerobic biodegradation

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Authors: Heming Yao

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Graphene-based percolative strain gauges could find applications in many places such as touch panels, artificial skins or human motion detection because of its advantages over conventional strain gauges such as flexibility and transparency. These strain gauges rely on a novel sensing mechanism that depends on strain-induced morphology changes. Once a compression or tension strain is applied to Graphene-based percolative strain gauges, the overlap area between neighboring flakes becomes smaller or larger, which is reflected by the considerable change of resistance. Tiny strain change on graphene-based percolative strain sensor can act as an important leverage to tremendously increase resistance of strain sensor, which equipped graphene-based percolative strain gauges with higher gauge factor. Despite ongoing research in the underlying sensing mechanism and the limits of sensitivity, neither suitable understanding has been obtained of what intrinsic factors play the key role in adjust gauge factor, nor explanation on how the strain gauge sensitivity can be enhanced, which is undoubtedly considerably meaningful and provides guideline to design novel and easy-produced strain sensor with high gauge factor. We here simulated the strain process by modeling graphene flakes and its percolative networks. We constructed the 3D resistance network by simulating overlapping process of graphene flakes and interconnecting tremendous number of resistance elements which were obtained by fractionizing each piece of graphene. With strain increasing, the overlapping graphenes was dislocated on new stretched simulation graphene flake simulation film and a new simulation resistance network was formed with smaller flake number density. By solving the resistance network, we can get the resistance of simulation film under different strain. Furthermore, by simulation on possible variable parameters, such as out-of-plane resistance, in-plane resistance, flake size, we obtained the changing tendency of gauge factor with all these variable parameters. Compared with the experimental data, we verified the feasibility of our model and analysis. The increase of out-of-plane resistance of graphene flake and the initial resistance of sensor, based on flake network, both improved gauge factor of sensor, while the smaller graphene flake size gave greater gauge factor. This work can not only serve as a guideline to improve the sensitivity and applicability of graphene-based strain sensors in the future, but also provides method to find the limitation of gauge factor for strain sensor based on graphene flake. Besides, our method can be easily transferred to predict gauge factor of strain sensor based on other nano-structured transparent optical conductors, such as nanowire and carbon nanotube, or of their hybrid with graphene flakes.

Keywords: graphene, gauge factor, percolative transport, strain sensor

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Authors: S. M. Yasir Arafat

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Driving models are needed by many researchers to improve traffic safety and to advance autonomous vehicle design. To be most useful, a driving model must state specifically what information is needed and how it is processed. So we developed an “Obstacle Avoidance and Detection Autonomous Car” based on sensor application. The ever increasing technological demands of today call for very complex systems, which in turn require highly sophisticated controllers to ensure that high performance can be achieved and maintained under adverse conditions. Based on a developed model of brakes operation, the controller of braking system operation has been designed. It has a task to enable solution to the problem of the better controlling of braking system operation in a more accurate way then it was the case now a day.

Keywords: automobile, obstacle, safety, sensing

Procedia PDF Downloads 364

Authors: Waroton Paisuwan, Mongkol Sukwattanasinitt, Mamoru Tobisu, Anawat Ajavakom

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Novel dihydroquinoline derivatives (DHP and DHP-OH) were synthesized in one pot via a tandem trimerization-cyclization of methylpropiolate. DHP and DHP-OH possess strong blue fluorescence with high quantum efficiencies over 0.70 in aqueous media. DHP-OH displays a remarkable fluorescence quenching selectively to the presence of Au3+ through the oxidation of dihydropyridine to pyridinium ion as confirmed by NMR and HRMS. DHP-OH was used to demonstrate the quantitative analysis of Au3+ in water samples with the limit of detection of 33 ppb and excellent recovery (>95%). This fluorescent probe was also applied for the determination of Au3+ residue in the gold nanoparticle solution and a paper-based sensing strip for the on-site detection of Au3+.

Keywords: Gold(III) ion detection, Fluorescent sensor, Fluorescence quenching, Dihydropyridine, Gold nanoparticles (AuNPs)

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Authors: Linara Salikhova, Elmira Nizamova, Aleksandra Katasonova, Gleb Vitkov, Olga Sarapulova.

Abstract:

While most European cities conduct research on heat-related risks, there is a research gap in the Caucasus region, particularly in Yerevan, Armenia. This study aims to test the method of establishing a correlation between urban heat islands (UHI) and urban greenery distribution for prioritization of heat-vulnerable areas for revegetation. Armenia has failed to consider measures to mitigate UHI in urban development strategies despite a 2.1°C increase in average annual temperature over the past 32 years. However, planting vegetation in the city is commonly used to deal with air pollution and can be effective in reducing UHI if it prioritizes heat-vulnerable areas. The research focuses on establishing such priorities while considering the distribution of urban greenery across the city. The lack of spatially explicit air temperature data necessitated the use of satellite images to achieve the following objectives: (1) identification of land surface temperatures (LST) and quantification of temperature variations across districts; (2) classification of massifs of land surface types using normalized difference vegetation index (NDVI); (3) correlation of land surface classes with LST. Examination of the heat-vulnerable city areas (in this study, the proportion of individuals aged 75 years and above) is based on demographic data (Census 2011). Based on satellite images (Sentinel-2) captured on June 5, 2021, NDVI calculations were conducted. The massifs of the land surface were divided into five surface classes. Due to capacity limitations, the average LST for each district was identified using one satellite image from Landsat-8 on August 15, 2021. In this research, local relief is not considered, as the study mainly focuses on the interconnection between temperatures and green massifs. The average temperature in the city is 3.8°C higher than in the surrounding non-urban areas. The temperature excess ranges from a low in Norq Marash to a high in Nubarashen. Norq Marash and Avan have the highest tree and grass coverage proportions, with 56.2% and 54.5%, respectively. In other districts, the balance of wastelands and buildings is three times higher than the grass and trees, ranging from 49.8% in Quanaqer-Zeytun to 76.6% in Nubarashen. Studies have shown that decreased tree and grass coverage within a district correlates with a higher temperature increase. The temperature excess is highest in Erebuni, Ajapnyak, and Nubarashen districts. These districts have less than 25% of their area covered with grass and trees. On the other hand, Avan and Norq Marash districts have a lower temperature difference, as more than 50% of their areas are covered with trees and grass. According to the findings, a significant proportion of the elderly population (35%) aged 75 years and above reside in the Erebuni, Ajapnyak, and Shengavit neighborhoods, which are more susceptible to heat stress with an LST higher than in other city districts. The findings suggest that the method of comparing the distribution of green massifs and LST can contribute to the prioritization of heat-vulnerable city areas for revegetation. The method can become a rationale for the formation of an urban greening program.

Keywords: heat-vulnerability, land surface temperature, urban greenery, urban heat island, vegetation

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Authors: An-Shik Yang, Chin-Ting Kuo, Yung-Chun Yang, Wen-Hsin Hsieh, Chiang-Ho Cheng

Abstract:

Optical biosensors have become a powerful detection and analysis tool for wide-ranging applications in biomedical research, pharmaceuticals and environmental monitoring. This study carried out the computational fluid dynamics (CFD)-based simulations to explore the dispersion phenomenon in the microchannel of a optical biosensor. The predicted time sequences of concentration contours were utilized to better understand the dispersion development occurred in different geometric shapes of microchannels. The simulation results showed the surface concentrations at the sensing probe (with the best performance of a grating coupler) in respect of time to appraise the dispersion effect and therefore identify the design configurations resulting in minimum dispersion.

Keywords: CFD simulations, dispersion, microfluidic, optical waveguide sensors

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Authors: Manta Nowbuth, Marie Anais Kimberley Therese

Abstract:

The vulnerability of coastal areas to storm surges stands as a critical global concern. The increasing frequency and intensity of extreme weather events have increased the risks faced by communities living along the coastlines Worldwide. Small Island developing states (SIDS) stands out as being exceptionally vulnerable, coastal regions, ecosystems of human habitation and natural forces, bear witness to the frontlines of climate-induced challenges, and the intensification of storm surges underscores the urgent need for a comprehensive understanding of coastal vulnerability. With limited landmass, low-lying terrains, and resilience on coastal resources, SIDS face an amplified vulnerability to the consequences of storm surges, the delicate balance between human activities and environmental dynamics in these island nations increases the urgency of tailored strategies for assessing and mitigating coastal vulnerability. This research uses an approach to evaluate the vulnerability of coastal communities in Mauritius. The Satellite imagery analysis makes use of sentinel satellite imageries, modified normalised difference water index, classification techniques and the DSAS add on to quantify the extent of shoreline erosion or accumulation, providing a spatial perspective on coastal vulnerability. The coastal Vulnerability Index (CVI) is applied by Gonitz et al Formula, this index considers factors such as coastal slope, sea level rise, mean significant wave height, and tidal range. Weighted assessments identify regions with varying levels of vulnerability, ranging from low to high. The study was carried out in a Village Located in the south of Mauritius, namely Rivière des Galets, with a population of about 500 people over an area of 60,000m². The Village of Rivière des Galets being located in the south, and the southern coast of Mauritius being exposed to the open Indian ocean, is vulnerable to swells, The swells generated by the South east trade winds can lead to large waves and rough sea conditions along the Southern Coastline which has an impact on the coastal activities, including fishing, tourism and coastal Infrastructures, hence, On the one hand, the results highlighted that from a stretch of 123km of coastline the linear rate regression for the 5 –year span varies from-24.1m/yr. to 8.2m/yr., the maximum rate of change in terms of eroded land is -24m/yr. and the maximum rate of accretion is 8.2m/yr. On the other hand, the coastal vulnerability index varies from 9.1 to 45.6 and it was categorised into low, moderate, high and very high risks zones. It has been observed that region which lacks protective barriers and are made of sandy beaches are categorised as high risks zone and hence it is imperative to high risk regions for immediate attention and intervention, as they will most likely be exposed to coastal hazards and impacts from climate change, which demands proactive measures for enhanced resilience and sustainable adaptation strategies.

Keywords: climate change, coastal vulnerability, disaster management, remote sensing, satellite imagery, storm surge

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Authors: Naghmeh M. Bandari, Javad Dargahi, Muthukumaran Packirisamy

Abstract:

Robot-assisted minimally invasive surgery (RMIS) has been widely performed around the world during the last two decades. RMIS demonstrates significant advantages over conventional surgery, e.g., improving the accuracy and dexterity of a surgeon, providing 3D vision, motion scaling, hand-eye coordination, decreasing tremor, and reducing x-ray exposure for surgeons. Despite benefits, surgeons cannot touch the surgical site and perceive tactile information. This happens due to the remote control of robots. The literature survey identified the lack of force feedback as the riskiest limitation in the existing technology. Without the perception of tool-tissue contact force, the surgeon might apply an excessive force causing tissue laceration or insufficient force causing tissue slippage. The primary use of force sensors has been to measure the tool-tissue interaction force in real-time in-situ. Design of a tactile sensor is subjected to a set of design requirements, e.g., biocompatibility, electrical-passivity, MRI-compatibility, miniaturization, ability to measure static and dynamic force. In this study, a planar optical fiber-based sensor was proposed to mount at the surgical grasper. It was developed based on the light intensity modulation principle. The deflectable part of the sensor was a beam modeled as a cantilever Euler-Bernoulli beam on rigid substrates. A semi-cylindrical indenter was attached to the bottom surface the beam at the mid-span. An optical fiber was secured at both ends on the same rigid substrates. The indenter was in contact with the fiber. External force on the sensor caused deflection in the beam and optical fiber simultaneously. The micro-bending of the optical fiber would consequently result in light power loss. The sensor was simulated and studied using finite element methods. A laser light beam with 800nm wavelength and 5mW power was used as the input to the optical fiber. The output power was measured using a photodetector. The voltage from photodetector was calibrated to the external force for a chirp input (0.1-5Hz). The range, resolution, and hysteresis of the sensor were studied under monotonic and harmonic external forces of 0-2.0N with 0 and 5Hz, respectively. The results confirmed the validity of proposed sensing principle. Also, the sensor demonstrated an acceptable linearity (R2 > 0.9). A minimum external force was observed below which no power loss was detectable. It is postulated that this phenomenon is attributed to the critical angle of the optical fiber to observe total internal reflection. The experimental results were of negligible hysteresis (R2 > 0.9) and in fair agreement with the simulations. In conclusion, the suggested planar sensor is assessed to be a cost-effective solution, feasible, and easy to use the sensor for being miniaturized and integrated at the tip of robotic graspers. Geometrical and optical factors affecting the minimum sensible force and the working range of the sensor should be studied and optimized. This design is intrinsically scalable and meets all the design requirements. Therefore, it has a significant potential of industrialization and mass production.

Keywords: force sensor, minimally invasive surgery, optical sensor, robotic surgery, tactile sensor

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Authors: Hossein Aghababaei, Sergio Vitale, Giampaolo Ferraioli

Abstract:

In the context of Synthetic Aperture Radar (SAR) data, polarization is an important source of information for Earth's surface monitoring. SAR Systems are often considered to transmit only one polarization. This constraint leads to either single or dual polarimetric SAR imaging modalities. Single polarimetric systems operate with a fixed single polarization of both transmitted and received electromagnetic (EM) waves, resulting in a single acquisition channel. Dual polarimetric systems, on the other hand, transmit in one fixed polarization and receive in two orthogonal polarizations, resulting in two acquisition channels. Dual polarimetric systems are obviously more informative than single polarimetric systems and are increasingly being used for a variety of remote sensing applications. In dual polarimetric systems, the choice of polarizations for the transmitter and the receiver is open. The choice of circular transmit polarization and coherent dual linear receive polarizations forms a special dual polarimetric system called hybrid polarimetry, which brings the properties of rotational invariance to geometrical orientations of features in the scene and optimizes the design of the radar in terms of reliability, mass, and power constraints. The complete characterization of target scattering, however, requires fully polarimetric data, which can be acquired with systems that transmit two orthogonal polarizations. This adds further complexity to data acquisition and shortens the coverage area or swath of fully polarimetric images compared to the swath of dual or hybrid polarimetric images. The search for solutions to augment dual polarimetric data to full polarimetric data will therefore take advantage of full characterization and exploitation of the backscattered field over a wider coverage with less system complexity. Several methods for reconstructing fully polarimetric images using hybrid polarimetric data can be found in the literature. Although the improvements achieved by the newly investigated and experimented reconstruction techniques are undeniable, the existing methods are, however, mostly based upon model assumptions (especially the assumption of reflectance symmetry), which may limit their reliability and applicability to vegetation and forest scenarios. To overcome the problems of these techniques, this paper proposes a new framework for reconstructing fully polarimetric information from hybrid polarimetric data. The framework uses Deep Learning solutions to augment hybrid polarimetric data without relying on model assumptions. A convolutional neural network (CNN) with a specific architecture and loss function is defined for this augmentation problem by focusing on different scattering properties of the polarimetric data. In particular, the method controls the CNN training process with respect to several characteristic features of polarimetric images defined by the combination of different terms in the cost or loss function. The proposed method is experimentally validated with real data sets and compared with a well-known and standard approach from the literature. From the experiments, the reconstruction performance of the proposed framework is superior to conventional reconstruction methods. The pseudo fully polarimetric data reconstructed by the proposed method also agree well with the actual fully polarimetric images acquired by radar systems, confirming the reliability and efficiency of the proposed method.

Keywords: SAR image, polarimetric SAR image, convolutional neural network, deep learnig, deep neural network

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Authors: Ashok Kumar Lonavath, V. Sathish Kumar

Abstract:

Urban sprawl is the uncontrolled and uncoordinated outgrowth of towns and cities. The process of urban sprawl can be described by change in pattern over time, like proportional increase in built-up surface to population leading to rapid urban spatial expansion. Significant economic and livelihood opportunities in the urban areas results in lack of basic amenities due to the unplanned growth The patterns, processes, dynamic causes and consequences of sprawl can be explored and designed with the help of spatial planning support system. In India context the urban area is defined as the population more than 5000, density more than 400 persons per sq. km and 75% of the population is involved in non-agricultural occupations. India’s urban population is increasing at the rate of 2.35% pa. The class I town’s population of India according to 2011 census is 18.8% that accounts for 60.4% of total unban population. Similarly in Erstwhile Andhra Pradesh it is 22.9% which accounts for 68.8% of total urban population. Suryapet town has historical recognition as ‘Gate Way of Telangana’ in the Indian State of Andhra Pradesh. The Municipality was constituted in 1952 as Grade-III, later upgraded into Grade-II in 1984 and to Grade-I in 1998. The area is 35 Sq.kms. Three major tanks located in three different directions and Musi River is flowing from a distance of 8 kms. The average ground water table is about 50m below ground. It is a fast growing town with a population of 1, 06,805 and 25,448 households. Density is 3051pp sq km, It is a Class I city as per population census. It secured the ISO 14001-2004 certificate for establishing and maintaining an environment-friendly system for solid waste disposal. It is the first municipality in the country to receive such a certificate. It won HUDCO award under environment management, award of appreciation and cash from Ministry of Housing and Poverty Elevation from Government of India and undivided Andhra Pradesh under UN Human Settlement Programme, Greentech Excellance award, Supreme Courts appreciation for solid waste management. Foreign delegates from different countries and also from various other states of India visited Suryapet municipality for study tour and training programs as part of their official visit Suryapet is located at 17°5’ North Latitude and 79°37’ East Longitude. The average elevation is 266m, annual mean temperature is 36°C and average rainfall is 821.0 mm. The people of this town are engaged in Commercial and agriculture activities hence the town has become a centre for marketing and stocking agricultural produce. It is also educational centre in this region. The present paper on urban sprawl is a theoretical framework to analyze the interaction of planning and governance on the extent of outgrowth and level of services. The GIS techniques, SOI Toposheet, satellite imageries and image analysis techniques are extensively used to explore the sprawl and measure the urban land-use. This paper concludes outlining the challenges in addressing urban sprawl while ensuring adequate level of services that planning and governance have to ensure towards achieving sustainable urbanization.

Keywords: remote sensing, GIS, urban sprawl, urbanization

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Authors: Rajeev Jain, Nimisha Jadon, Kshiti Singh

Abstract:

Titanium oxide nanoparticles and 1-butyl-2,3-dimethylimidazolium bis (trifluoromethane- sulfonyl) imide modified glassy carbon electrode (TiO2/IL/GCE) has been fabricated for electrochemical sensing of flunarizine dihydrochloride (FRH). The electrochemical properties and morphology of the prepared nanocomposite were studied by electrochemical impedance spectroscopy (EIS) and transmission electron microscopy (TEM). The response of the electrochemical sensor was found to be proportional to the concentrations of FRH in the range from 0.5 µg mL-1 to 16 µg mL-1. The detection limit obtained was 0.03 µg mL-1. The proposed method was also applied to the determination of FRH in pharmaceutical formulation and human serum with good recoveries.

Keywords: flunarizine dihydrochloride, ionic liquid, nanoparticles, voltammetry, human serum

Procedia PDF Downloads 329

Authors: Yogesh Kumar Singh, T. S. Murugesh Prabhu, Upasana Dutta, Girishchandra Yendargaye, Rahul Yadav, Rohini Gopinath Kale, Binay Kumar, Manoj Khare

Abstract:

The Indian subcontinent is severely affected by floods that cause intense irreversible devastation to crops and livelihoods. With increased incidences of floods and their related catastrophes, an Early Warning System for Flood Prediction and an efficient Flood Management System for the river basins of India is a must. Accurately modeled hydrological conditions and a web-based early warning system may significantly reduce economic losses incurred due to floods and enable end users to issue advisories with better lead time. This study describes the design and development of an EWS-FP using advanced computational tools/methods, viz. High-Performance Computing (HPC), Remote Sensing, GIS technologies, and open-source tools for the Mahanadi River Basin of India. The flood prediction is based on a robust 2D hydrodynamic model, which solves shallow water equations using the finite volume method. Considering the complexity of the hydrological modeling and the size of the basins in India, it is always a tug of war between better forecast lead time and optimal resolution at which the simulations are to be run. High-performance computing technology provides a good computational means to overcome this issue for the construction of national-level or basin-level flash flood warning systems having a high resolution at local-level warning analysis with a better lead time. High-performance computers with capacities at the order of teraflops and petaflops prove useful while running simulations on such big areas at optimum resolutions. In this study, a free and open-source, HPC-based 2-D hydrodynamic model, with the capability to simulate rainfall run-off, river routing, and tidal forcing, is used. The model was tested for a part of the Mahanadi River Basin (Mahanadi Delta) with actual and predicted discharge, rainfall, and tide data. The simulation time was reduced from 8 hrs to 3 hrs by increasing CPU nodes from 45 to 135, which shows good scalability and performance enhancement. The simulated flood inundation spread and stage were compared with SAR data and CWC Observed Gauge data, respectively. The system shows good accuracy and better lead time suitable for flood forecasting in near-real-time. To disseminate warning to the end user, a network-enabled solution is developed using open-source software. The system has query-based flood damage assessment modules with outputs in the form of spatial maps and statistical databases. System effectively facilitates the management of post-disaster activities caused due to floods, like displaying spatial maps of the area affected, inundated roads, etc., and maintains a steady flow of information at all levels with different access rights depending upon the criticality of the information. It is designed to facilitate users in managing information related to flooding during critical flood seasons and analyzing the extent of the damage.

Keywords: flood, modeling, HPC, FOSS

Procedia PDF Downloads 89

Authors: Hossein Aghababaei, Sergio Vitale, Giampaolo ferraioli

Abstract:

In the context of Synthetic Aperture Radar (SAR) data, polarization is an important source of information for Earth's surface monitoring . SAR Systems are often considered to transmit only one polarization. This constraint leads to either single or dual polarimetric SAR imaging modalities. Single polarimetric systems operate with a fixed single polarization of both transmitted and received electromagnetic (EM) waves, resulting in a single acquisition channel. Dual polarimetric systems, on the other hand, transmit in one fixed polarization and receive in two orthogonal polarizations, resulting in two acquisition channels. Dual polarimetric systems are obviously more informative than single polarimetric systems and are increasingly being used for a variety of remote sensing applications. In dual polarimetric systems, the choice of polarizations for the transmitter and the receiver is open. The choice of circular transmit polarization and coherent dual linear receive polarizations forms a special dual polarimetric system called hybrid polarimetry, which brings the properties of rotational invariance to geometrical orientations of features in the scene and optimizes the design of the radar in terms of reliability, mass, and power constraints. The complete characterization of target scattering, however, requires fully polarimetric data, which can be acquired with systems that transmit two orthogonal polarizations. This adds further complexity to data acquisition and shortens the coverage area or swath of fully polarimetric images compared to the swath of dual or hybrid polarimetric images. The search for solutions to augment dual polarimetric data to full polarimetric data will therefore take advantage of full characterization and exploitation of the backscattered field over a wider coverage with less system complexity. Several methods for reconstructing fully polarimetric images using hybrid polarimetric data can be found in the literature. Although the improvements achieved by the newly investigated and experimented reconstruction techniques are undeniable, the existing methods are, however, mostly based upon model assumptions (especially the assumption of reflectance symmetry), which may limit their reliability and applicability to vegetation and forest scenarios. To overcome the problems of these techniques, this paper proposes a new framework for reconstructing fully polarimetric information from hybrid polarimetric data. The framework uses Deep Learning solutions to augment hybrid polarimetric data without relying on model assumptions. A convolutional neural network (CNN) with a specific architecture and loss function is defined for this augmentation problem by focusing on different scattering properties of the polarimetric data. In particular, the method controls the CNN training process with respect to several characteristic features of polarimetric images defined by the combination of different terms in the cost or loss function. The proposed method is experimentally validated with real data sets and compared with a well-known and standard approach from the literature. From the experiments, the reconstruction performance of the proposed framework is superior to conventional reconstruction methods. The pseudo fully polarimetric data reconstructed by the proposed method also agree well with the actual fully polarimetric images acquired by radar systems, confirming the reliability and efficiency of the proposed method.

Keywords: SAR image, deep learning, convolutional neural network, deep neural network, SAR polarimetry

Procedia PDF Downloads 90

Authors: Prem K. Mony, Bharadwaj Amrutur, Prashanth Thankachan, Swarnarekha Bhat, Suman Rao, Maryann Washington, Annamma Thomas, N. Sheela, Hiteshwar Rao, Sumi Antony

Abstract:

The disease burden among mothers and newborns is caused mostly by a handful of avoidable conditions occurring around the time of childbirth and within the first month following delivery. Real-time monitoring of vital parameters of mothers and neonates offers a potential opportunity to impact access as well as the quality of care in vulnerable populations. We describe the design, development and testing of an innovative wearable device for remote biomonitoring (RBM) of body temperatures in mothers and neonates in a hospital in southern India. The architecture consists of: [1] a low-cost, wearable sensor tag; [2] a gateway device for ‘real-time’ communication link; [3] piggy-backing on a commercial GSM communication network; and [4] an algorithm-based data analytics system. Requirements for the device were: long battery-life upto 28 days (with sampling frequency 5/hr); robustness; IP 68 hermetic sealing; and human-centric design. We undertook pre-clinical laboratory testing followed by clinical trial phases I & IIa for evaluation of safety and efficacy in the following sequence: seven healthy adult volunteers; 18 healthy mothers; and three sets of babies – 3 healthy babies; 10 stable babies in the Neonatal Intensive Care Unit (NICU) and 1 baby with hypoxic ischaemic encephalopathy (HIE). The 3-coin thickness, pebble-design sensor weighing about 8 gms was secured onto the abdomen for the baby and over the upper arm for adults. In the laboratory setting, the response-time of the sensor device to attain thermal equilibrium with the surroundings was 4 minutes vis-a-vis 3 minutes observed with a precision-grade digital thermometer used as a reference standard. The accuracy was ±0.1°C of the reference standard within the temperature range of 25-40°C. The adult volunteers, aged 20 to 45 years, contributed a total of 345 hours of readings over a 7-day period and the postnatal mothers provided a total of 403 paired readings. The mean skin temperatures measured in the adults by the sensor were about 2°C lower than the axillary temperature readings (sensor =34.1 vs digital = 36.1); this difference was statistically significant (t-test=13.8; p<0.001). The healthy neonates provided a total of 39 paired readings; the mean difference in temperature was 0.13°C (sensor =36.9 vs digital = 36.7; p=0.2). The neonates in the NICU provided a total of 130 paired readings. Their mean skin temperature measured by the sensor was 0.6°C lower than that measured by the radiant warmer probe (sensor =35.9 vs warmer probe = 36.5; p < 0.001). The neonate with HIE provided a total of 25 paired readings with the mean sensor reading being not different from the radian warmer probe reading (sensor =33.5 vs warmer probe = 33.5; p=0.8). No major adverse events were noted in both the adults and neonates; four adult volunteers reported mild sweating under the device/arm band and one volunteer developed mild skin allergy. This proof-of-concept study shows that real-time monitoring of temperatures is technically feasible and that this innovation appears to be promising in terms of both safety and accuracy (with appropriate calibration) for improved maternal and neonatal health.

Keywords: public health, remote biomonitoring, temperature surveillance, wearable sensors, mothers and newborns

Procedia PDF Downloads 208