The objective of the proposed application is to create a platform for asset tracking in the trucking industry that operates under a subscription-based software-as-a-service (SaaS) model. It has a mobile app for drivers that helps with dispatching pick-up and delivery locations and calculating total miles driven over a period of time covering duration and trips and a web-based interface for carriers, brokers, and the company.

The platform is integrated with a third-party hardware device that tracks various data points such as vehicle location, door opening, temperature, and humidity in real-time. The data collected by this device is sent back to cloud-based services that can be accessed via cloud-based APIs or the SDK provided by the device manufacturer.

Build this proposed asset wear management solution that assists owners (Shovels, undercarriage, etc) in managing the wear of the asset and getting full the most out of them. The software enables enterprises to achieve maximum availability and optimal life from their crawler undercarriage as the Undercarriage/shovels are high-value wear items and can cost large maintenance amounts and installation.

The software can be used by users across different industries in Fleet/Asset rental companies: Renting moveable equipment, 3rd Party Inspection companies, and Construction/mining companies to manage their asset/fleet wear, Gas & petroleum companies, and Equipment Fabrication/manufacturing industries.
 

This project is based on OCR using python. The data from documents (hand written or scanned), images, excel, CSV is read and converted into structured data using NLP (natural language processing) and natural language tool kit (NLTK). Important data fields related to patient's visit to clinic or hospital are extracted and stored for further analytics.

The application makes it easier for mental health patients to search and match with licensed therapists for in-person or video-based consultations. The application also connects therapists to a network of new patients, helps with payor credentialing, manages billings and claims processes, manages dynamic assessments, and guarantees instant payment on claims.

The Platform project aims to revolutionize the way patients and doctors connect for immediate consultations. Implementing first-in, first-out (FIFO) approach, the platform prioritizes patients based on the order of their requests, reducing wait times and enhancing patient satisfaction. Patients can provide detailed information about their symptoms, upload relevant images, and specify the type and duration of consultation they need, empowering doctors to make accurate diagnoses and treatment recommendations during video consultations. The platform ensures seamless and secure interactions, allowing patients to rejoin the queue if they accidentally close their browser. It also simplifies the prescription process with a secure payment gateway and facilitates the delivery of prescriptions. 

The Platform project aims to enhance accessibility to healthcare services, optimize patient-doctor interactions, and elevate the overall quality of care. By leveraging technology and incorporating innovative features, the platform strives to provide a seamless experience for patients and doctors alike. With its focus on efficient queue management, comprehensive patient information, secure interactions, and simplified prescription processes, the Platform aims to revolutionize the way healthcare consultations are conducted, improving access to care and facilitating better healthcare outcomes.

Imaging Systems for Aesthetics and Dermatology. Works in the field of aesthetics and early skin cancer detection, using imaging procedures. Business focus is on the development, image management, archiving, and sale of systems for digital aesthetics, dermatoscopy, and body mapping procedures. 

We are developing a cloud based solution to integrate new features into the desktop-based medical imaging (SAAS) platform. The application is presently designed to view images and analyse them thereby aiding in the detection of a wide array of dermatological pathologies. 

Desktop based application is getting migrated to a cloud-based architecture to provide uniform access from various platforms like Macintosh, Microsoft, iPad, and mobile devices.  We also utilize our AI-ML skills in improving image analysis, interoperability, reliance on non-cloud apps, integration of various in-house hardware devices, etc. all factors that will be accommodated while optimizing overall application performance.