Label Extraction and AI for Digital PathologyTissue-based studies generate large amounts of histology data containing important biological information in the form of imagery and metadata.These digital pathology slides are labeled using text and barcodes for their identification.The older technologies used printed or handwritten labels for specimen labeling.The Label Extraction Solution uses state-of-the-art OCR technologies, image processing, and AI to read, understand, and store label data from digital pathology slides.Additional manual validation of the data leads to a highly automated process which reduces the time to search and find slides.The extracted label text is translated into a structured data format, stored in a database with search capabilities.
In the time of the global pandemic, pharma companies have resorted to massive clinical research and development to produce an effective vaccine against the deadly coronavirus.This makes one wonder how evolved are the Pharma companies to deal with every changing healthcare scenario.Many of the Pharma companies have replaced traditional ways of managing the manufacturing floor and their day-to-day operations.They are knowledgeable and have access to data about healthcare and expect the best from the pharma companies.Few examples can be cited – Doctors expect new products to exceed their performance as compared to existing products.Patients want their opinions to be heard during the developmental stage of new medicine.Insurance companies want cost-effective products.Data SourcesThe first and foremost requirement for any change is information or data.
There was no looking back since then.From a car with no windshields and steering wheel, we now have a driverless car!Introduction of Self-Driving VehiclesThe idea of the self-driving vehicle was introduced by General Motors in the year 1939.It was a radio-controlled electric vehicle.An autonomous vehicle uses a combination of sensors, artificial intelligence, radars, and cameras to operate, without any human intervention.AI helps computers to decode and understand the visual data acquired from various sources.This is useful to track and also predict behavioral patterns of other drivers and to make driving safe.Lane line DetectionCutting lanes can prove to be a disaster in the case of self-driving vehicles.
It is used to monitor climate conditions, for aerial photography, video inspection, aerial mapping, drone delivery, and more.In recent times it is used for search & rescue operations post any natural disasters.It is best to locate a missing or kidnapped person in a vast area.How is search and rescue operations carried out using drone image?Individual rescue using Drone ImageryThe real-time imagery provides crucial information about emergencies.It provides an accurate location over a vast area so that rescuers can take quick decisions and act on it immediately.They can send the team to specific areas where help is needed.Drones can use floodlights to carry out nighttime rescue operations.The footage of search and rescue is used for future training purposes as well.Hazardous Chemical SpillsIn case of hazardous chemical spills or leakage of nuclear chemicals from factories, damage assessment can be a risky task.
A combination of social, economic, legal, and administrative parameters leads, in several countries, to the stage of unplanned development and to the creation of a considerable number of illegal buildings.
The owners may be charged with high penalties, also such properties cannot be transferred or mortgaged, while there is always a risk of creating an informal market, and
In the case of a massive scale, they may have a negative environmental effect.
Classic administrative control procedures are proved inefficient, especially when public administration suffers from a lack of employees, bureaucracy, and increased responsibilities.
The focus of this project is restricted only to the 1st category – constructions without a building permit- and on buildings at the urban fringe or generally in areas without urban plans, which gradually create unplanned settlements.
In areas without urban plan construction is only permitted inland parcels bigger than 0.4 ha and only for a building size up to 200 sq.m.
The lack of cadastre in such countries has a multidimensional impact on land management issues.
Keeping this in mind the U.S Food and Drug Administration (FDA), as well as the European Medicines Agency (EMA), recently issued revised guidelines.Process Validation is where recurring data is analyzed on a periodic basis and is the primary part of process validation.The Process Validation is conducted in 3 stages: Stage 1 is the Process design; Stage 2 is the Process Qualification and Stage 3 is the Continued Process Verification.Thus, it allows identifying any deviation from the process if any.The following are the CPV challenges faced by pharmaceutical industries today.Inaccuracies in PaperworkMany companies used manual processes for recording data batches.Hence, they face data entry issues, missed signatures, and incomplete details on the form.All this leads to a delay in CPV and makes it cumbersome.Zero TraceabilityCompanies that rely on manual CPV find it difficult to trace manufacturing changes.
OpportunityChemical supply chains forced to adapt to new expectationsAs global commerce continues to make its migration from “the main street” to “mainframe”, organizations across all industries have been investing vigorously in ways to digitize their operations.eCommerce has become a norm in everyday life for most consumers, and as expectations for the same frictionless experience continue to make their way towards other industries, the chemicals industry has been no exception.The next generation of purchasing managers increasingly values speed, transparency, and ease of doing business above other factors.Despite this fact, eCommerce adoption in the industrial B2B setting has been evolving at a much slower pace when compared to industries that sell directly to consumers.Industrial manufacturing companies are challenged with the changes needed to existing habits, processes, and systems, to adapt to the evolving expectations.A few years ago, one company that had been manufacturing and distributing high purity chemical products for over 25 yearsrecognized that the traditional way of doing business was no longer able to keep up with the evolving needs of customers and suppliers.Too many links in the chemical supply chain, combined with manual processes along the way, not only prevents companies from delivering a better customer experience, but also limits the visibility and insights that manufacturers need to optimize inventory and production.What was needed was a truly digital point of sale and supply chain experience for all stakeholders involved, capable of providing real-time pricing, inventory, and demand signals.To stay in front of the competition, the company asked Aventior to help design, develop, and launch the first truly digital marketplace for the chemical industry.SolutionCombining scalability with industry-specific needsOver the course of 10 months, Aventior had completed the design, development, and launch of the industry’s first truly digital eCommerce marketplace for the chemical industry.With scalability and user experience at the forefront, the platform also needed to incorporate specific features and functionality to support the chemicals industry.Third-party connectivity was another critical component of the platform – it had to be capable of sending and receiving information seamlessly with external systems to deliver an end-to-end digital experience, whether it be with logistics providers, suppliers, buyers, and other third-party tools.
It is important as it helps to identify existing or/and potential hazards.Many of these lines are inaccessible due to a lack of transportation and geographical locations.The undetected faulty gas lines and power lines had led to a forest fire.They also face certain limitations such as inaccessible terrain, contact with high-voltage power lines, hazardous chemicals emission, and more.Using Drones for Utility InspectionsDue to the above, many companies have started to use drones as the inspectors can survey the structures or lines from a safe distance and can cover difficult terrains & conditions with ease.Few examples of utility inspections carried out using drones are:Power transmission line– to identify foliage encroachment, sagged wires, fuels buildup that leads to forest firesVertical constructions– to check signs of irregularities and damageBridges & overpass– to check signs of damage or cracksWater systems– to identify leakages, management of vegetationDams– to check structural defects and identify the repairs neededDrones improve the quality of such inspection as it allows the inspectors to conduct frequent inspections and to collect more data.Thermal imagery, hyperspectral, color, light detection & ranging are the sensors used.
When these modes of transport carry so much material, it becomes crucial to monitor and track their movement across the globe.Satellite Image analysis provides a great solution to such problems.These image analysis not only help in tracking the given subject but also helps in monitoring the surroundings of the target.With ships detection, and combined with data of other ships routes and live status, (Data from other sources), many security features can be built.Also, search and rescue operations can be further improved in terms of their response time and location accuracy.These Applications require large quantities of data, and with the recent availability of satellite images from many tech giants and government organizations, it has become an emerging field in the aerospace domain.Rhammell on Kaggle provided a cleaned dataset of satellite imagery, separately for each of the categories, i.e.Images were derived from PlanetScope full-frame visual scene products, which were ortho-rectified to 3-meter pixel size.
Water is the vital natural resource for human survival and development, as well as an important restriction factor of the Eco-environment.It is not only critical to the ecosystems as a key component of the hydrologic cycle but also touches every aspect of our lives, such as drinking water, agriculture, electricity production, transportation, and industrial purposes.Surface water bodies are dynamic as they shrink, expand, or change their appearance or course of flow with time, owing to different natural and human-induced factors.Change in surface water volume usually causes serious consequences.The spatial and temporal change pattern of the surface water has important practical significance and scientific value for water resources management, biodiversity, emergency response, and global climate change.However, small water bodies such as small ponds and narrow rivers cannot be extracted due to the limited spatial resolution of these remote-sensing images.Most high-resolution remote-sensing images only have four bands (blue, green, red, and near-infrared), lacking the short-wave infrared (SWIR) data necessary to compute the modified normalized difference water index (MNDWI) and the automated water extraction index (AWEI) indices.A high-resolution spatial multi-spectral image has more detailed spatial features information, which can greatly improve the accuracy of urban water body extraction.
Life ScienceAventior has been working with some of the leading pharma, biotech, and diagnostics companies providing the technical know-how and support to build their digital ecosystem.With a significant focus on harnessing the power of data for drug research, clinical trials, and drug manufacturing, leading life sciences companies are building solutions that will help them achieve faster go-to-market solutions.Additionally, Aventior is also helping develop solutions for telehealth and eCOA.In the current pandemic the popularity of telehealth systems, mobile apps for patient and physician interaction, remote monitoring, real-time analytics are becoming increasingly important.These technologies also help retain patients longer for clinical trials and overall improve the end-user experience by reducing the number of time patients have to spend at clinics.The use of AI for drug discovery, pre-clinical and clinical data analysis, RWE and patient recruitment, pharmacovigilance, clinical imaging analysis, digital pathology, and commercialization is becoming increasingly important.Companies are using AI to reduce their cost of drug development, identifying new molecules faster, recruit the right patient and retain them during clinical trials.Life Science Solutions by AventiorData Restructuring and Analytics Platform (DRIP)DRIP integrates data from disparate sources and creates a universal database for easy data visualization.Read moreContinued Process Verification (CPV) - AutoCPV - Auto is an AI-based automation platform for processing pharma/biotech compliance documents.
Chemicals and Active Pharmaceutical Ingredients (API)Digitalization is a boon to this era and has not left any sector untouched; one of them is the chemical industry.In recent years and especially during these COVID times, many chemical companies have opted for digital approaches to maintain a competitive edge and embrace new market opportunities.To showcase themselves, many companies have started using the digital platform.These platforms help companies to offer the chemicals across two customer bases i.e.Among these two customer bases, it is being observed that the B2B buyers mostly prefer using the digital platform leaving behind the traditional method of placing orders for bulk chemicals, APIs, and specialty chemicals through phones or emails.The chemical industries have embraced digital technology to expand their profit margin.
Aventior architects design and builds a solution to integrate local storage appliances with the scale of the cloud for one of the top data storage companies in the worldOpportunityIn the age of information, where do we keep all the dataData storage is a critical aspect of any business.Businesses of all sizes are faced with an increasing amount of data, and it is not only attributed to economic growth – companies are constantly discovering new ways to leverage data to refine their products, services, and analyze customer behavior, which means more data needs to be both captured and stored.It allows businesses large and small to simplify data management, maximize server performance, back up critical data, and increase application availability.For this reason, the use of storage area networks or SAN remains common when it comes to enterprise data storage management solutions.SANs are essentially dedicated networks connecting data storage tools with larger networks, facilitating the pooling of storage among data centers.However,companies that specialize in enterprise storage solutions have now caught on to the potential benefits of integrating locally hosted storage appliances with the benefits offered by cloud storage solutions.ApproachIntegrating local storage appliances with the scale of the cloudThe solution developed by Aventior would utilize a combination of AWS CloudFormation and AWS IoT Greengrass to create a dynamic and infinitely scalable architecture to support the desired functionality.AWS CloudFormation allows the use of programming languages in the modeling and provisioning of the resources needed for applications.
Since the inception, the most widely used techniques for inspection are the manual inspection which includes either foot patrol or/and conventional helicopter-based inspection.The detailed approaches used for segmentation, object detection, and anomaly detection are described in the following section.Powerlines SegmentationThe Powerlines Segmentation is used to separate the powerlines (the power transmission cables) from the entire image so that an inspection algorithm can just focus and analyze only the power lines while staying unaffected by the surrounding or the background of the powerlines.It consists of convolutional layers on skip pathways which bridges the semantic gap between encoder and decoder feature maps, thus aiding in improving the gradient flow.DatasetsDataset 1:We have obtained 200 Visible Light (VL) spectrum images from the https://data.mendeley.com/datasets/twxp8xccsw/1.It consists of 200 images of size 512×512, along with the binary wired image masks for all the input images.Dataset 2:The other set of images was obtained from https://data.mendeley.com/datasets/n6wrv4ry6v/8.Further, data augmentations were carried out on Dataset 2 same as Dataset 1.Training and Segmentation Methodology Nested U-Net architecture, as the name implies, makes use of nested and dense skip connections between encoder and decoder apart from the typical skip connection used in U-Net Network.Like the IoU, they both range from 0 to 1, with 1 signifying the greatest similarity between predicted and truth.
Resolution Reconstruction of Urban Images (Satellite Images) using AIIt is said that “A picture is worth a thousand words”.Computers can understand these images in terms of color values at a pixel level, and the features of the contents.The CV has now become a popular topic of academic and industrial research applications.The quality of the image is dependent on the sensors which capture these images, and sensors can be very expensive if extremely high image quality is expected.With Artificial Intelligence (AI) it is now possible to improve the image quality up to a certain extent, without much loss of data.The quality of images produced by sensors is limited, mostly due to sensor hardware limitations which cannot be much experimented with, as the sensor hardware is a costly piece in the system.One such important type of enhancement is resolution improvement, especially in the field of Satellite Imagery.In satellite images, the image resolution denotes the distance on the ground that is captured by each pixel.
It is easy to log in to the app rather than logging into their website via desktop.He can also get feedback for the services provided and clock-in his work hours.Payment Facilitation using the SmartphoneCash-free transactions are been encouraged across the world.They can choose the number of assignments they want to take-up & also cater to their personal responsibilities simultaneously.Airbnb, for example, allows house owners to confirm guest booking & receive payments easily through their smartphone when they would be trotting across the globe.Beneficial for Business OwnersThe business owner need not invest in office space & get infrastructure for freelance workers or contractors.Businesses save a huge amount on office space rentals & other infrastructure.Businesses can invite quotes from professionals across the world & get quotes as per their budget.
In today’s world, advancement in technology is resulting in customers expecting a very intuitive shopping experience.Digital eCommerce platforms and application leaders should focus on these key capabilities which will impact its future.Technology will help them differentiate from their competitors and attract new customers in the following ways: A B2C experience has become ubiquitous, and today all B2B customers expect a B2C shopping experience.Capabilities need to be prioritized based on “business value” and “ease of implementation”.Digital eCommerce capabilities that will not add significant business value to end customers and have higher implementation costs should be pushed back.A customer experience that incorporates interactive and conversational visual interface has a bigger impact on the conversion funnel.Unified commerce experience across all channels and throughout the customers’ shopping journey offers flexibility and consistency to deliver a superior customer experience.New business models such as IoT enabled eCommerce, enterprise marketplaces, subscription and replenishments can help companies move toward digital eBusiness from a completely new perspective, there are new digital technologies which can enable these capabilities with a faster time to market.AI (Artificial Intelligence), personalization engines, guided selling, API-oriented architecture, and product configurators are key technologies and architecture that enable compelling customer experience and digital business models.Persona and scenario-based customer experience coupled with new eBusiness models have a critical impact on the success of digital e-commerce.Persona-based customer experience not only differentiates digital e-commerce offerings but also results in increased conversion rates and repeat purchases.Digital e-commerce is getting more visual.People can find similar products using visual search.They can buy directly from streaming video with identifiable goods or from social media images using buy buttons, or view customizable products in 2D/3D using configurators.
In spite of rising demand for the creation of digital data directly at the source itself, some companies follow the traditional methods of documenting the processes parameters on paper, on designed forms.This leads to data being inaccessible for others unless it is again digitized by someone.Keeping data on papers has its own set of limitations like limited accessibility, searchability, using data for analytics, etc.Digital Transformation of DocumentsThe digital transformation of such documents is necessary.The manual data entry process consumes valuable time and effort from the scientists while explaining the entire process of data entry to new interns consumes time from the team.With advancements in the software industry, there have been multiple attempts to solve these problems, but each solution comes with its own set of limitations.Robotic Process Automation (RPA)Robotic Process Automation (RPA) is one of the closest successful solutions in helping companies convert their data from papers to structured digital formats.The software tries to identify the set of parameters on the image, which need to be translated into the structured database.
Biotech, Pharmaceutical, and Life Sciences companies face significant challenges in integrating data from a variety of sources.Drug research and testing is one of the biggest data producers and the inability to ingest, structure, and search data from labs, CROs, and the field make data interpretation a highly inefficient process.Aventior’s DRIP uses a combination of complex machine learning (ML) and rule-based algorithms to automate the data ingestion, integration, and formatting.Using proprietary pattern recognition algorithms and metadata comprehension, DRIP builds a consolidated database of research data and lab results.Irrespective of the nature of the source data (structured or unstructured) DRIP is capable of transforming the source data into a usable format while maintaining strict control over the quality of data transformation.The platform also enables data visualization and exploration using its own extension, that can be hosted on cloud platforms.DRIP also supports integration with some of the leading data visualization platforms such as TIBCO Spotfire and Tableau or custom R/Shiny applications.