MEDBOT IOT


Introduction

At Girls in Tech, the main barriers to adopting IOT technologies are security, ease of integration with legacy systems, and return on investment. Medbot addresses these concerns with the use of emerging technologies (computer vision, natural language processing, and blockchain) controlled via a web interface and a robots-as-a-service business model.

Seniors can connect to the internet and integrate with Medbot's advanced smart home technology with innovative use of AI-powered medical robots on the blockchain. Medbot is a solution for smart household aging in place environments by using Arduino IoT controlled by web and mobile interfaces. This exchange of medical information encompasses IoT technologies which include data, software, and hardware while addressing concerns regarding cybersecurity, coexistence, compliance, connectivity, and cloud.


Purpose & Motivation

As the IoT market grows to $520 billion during the current state of our community during the global pandemic - there has never been a more important time to engineer medical devices for seniors aged 65+. Seniors who are more vulnerable to health conditions represent 5% of population yet 42% of the $3.8 trillion healthcare industry. For many seniors who live in low density rural areas, access to doctors is difficult and can takes on average 4 weeks in the United States.

Solving remote healthcare addressing a large medical issue in society which affects many people daily, yet is often overlooked. Medbot solution can potentially contribute to the improvement of the medical system. The solution is to build smart spaces for senior care aging in place with a focus on the following pain points.

  • Autonomy - they want to stay independent with physical mental and financial freedom
  • Safe spaces - reduce environmental risks and homes while supporting mobility
  • Long-term health - identify health risks managed multiple medications and chronic illnesses
  • Social connection - relationships with friends and family

Healthcare professionals who access the patient's information through the institution's certified database which can securely offload data from the blockchain. This interface can allow all professionals to have immediate access to patient history and conduct data analysis without changing the data itself. Seniors have a separate interface which allows them to read-only, but have complete access to their own personal history. This increases transparency between medical professionals and patients and allows patients. Information on user friendly web and mobile interfaces to allow for a positive user experience for all stakeholders.


How was the application developed?

All the code is open-sourced and easily assessible on github: https://github.com/lucylow/medblock. Refer to the technical architecture diagram for how the IOT application was developed.

RFID sensors with location tracking for safety with checkpoints. This feature locates missing items with software hardware connectivity IOT - MedBot Robot for home monitoring and medical alerts/notifcations. Each Medbot robot is connected to an arduino which can integrate with the web/mobile interface. Serverless IoT architecture includes tagging valuable objects with RFID tags to make them easily locatable this provides Peace of Mind as we're able to support independent living promoting safer more accurate remove healthcare for seniors. Arduino IOT hub integrated with ROS was required to run with audio and visual sensors. These sensors allow remote healthcare to be delivered to seniors from stakeholders.

Computer vision with three tensorflow models medical diagnosis and automated pill box and fall detection these features allow those with visual impairments to use their smart devices to navigate around their homes and will enhance the sight seniors already have. Computer Vision with Tensorflow.js with an automated pillbox fall detection, visual impairment aid, and remote medical diagnostics. Natural language processing with Tensorflow JS and Open AI's GPT3 - speech recognition, text to command, voice activation, and a chatbot to combat social isolation. Hardware is also attached to an audio sensor allowing for natural language processing capabilities liketext to command and a chat bot feature with voice activation powered by GPT3.

One of the main problems with remote medical healthcare is the way highly identifiable sensitive medical patient's data is stored. Instead of records in physical files, we have EPR - an Electronic Patient Record system. Blockchain medical data with Robonomics encryption on top of Polkadot and IPFS - allows for data privacy and endpoint security for controlling robotics from distributed clouds. Considerations made for cybersecurity, compliance, connectivity, interoperability, reliability, and single point of failure while leveraging cloud technologies. Blockchain technology to store patient profiles within block ledgers to securely store all historical data about a patient like examinations, medical procedures, lab tests, and medications anywhere with the patient's permission. Currently, most IoT and robotics applications are usually organized under a centralized cloud control. Medbot is built on the Ethereum blockchain for a secure way to transfer and centralize patient data to allow access to patient data for all certifies healthcare institutions and patients. Using blockchain encryption for data privacy and point security in order to protect personal identities online. Medical data remains secure and authentic, maintaining data integrity and a chain of trust.


How to use the application

Code for the mobile/web application is live and running on https://lucylow.com/medblock/

The system of medical robots supports general sets of sensors and virtual devices that makes software-hardware interaction easy. The main barriers of adopting IOT technologies are security, ease of integration with legacy systems, and return on investment. Medbot addresses these concerns with the use of emerging technologies (computer vision, natural language processing, and blockchain) controlled via a web interface and a robots-as-a-service business model. This allows for decentralized cloud systems for robotics control on an open source Web3 platform. The existing public blockchain infrastructure and connects with Arduino's ecosystem. This enables the exchange of medical information between humans and robots for internet of things.

Medbot protocol, a peer to peer communication network is created for medical robot application. The peer to peer protocol and the use of smart contracts with uniform authorization protocols is transport agnostic allowing access to healthcare information for remote seniors. IPFS is a content-based distribution system and uses cryptographically verifiable hashes so this can store images like medical radiographs for medical diagonsis. This works by sending bio-metric data to IPFS and hash storing in chain options with nodes. Token-based authentication will help with security, where the token is a random IPFS hash assigned to the user and they can reset it at any point if it has been stolen. Allow the token to be passed in through the Medbot network. Each transaction must be signed by account's unique seed. It has two forms: Mnemonic that is human-readable and raw that is a sequence of digits and letters. By using smart contracts and Blockchain technology, it provides secure integration of IOT cyber-physical systems into the healthcare economy with seamless connectivity enabling distributed cloud technology for medical robotics.


Difficulties & Challenges faced during the design and/or development process

  • Using tutorials for setting up Arduino IOT environment, creating sketches and hardware integration and the phone-Arduino link integration of IoT devices with legacy systems
  • Fall detection binary image classification algorithm with tensorflow.js pose algorithms was hard to make
  • Research more about healthcare privacy and legal regulations
  • Doctors will get notified to respective patient via SMS or Mail
  • Wanted to add Multilingual Support considerations for user experience and diversity and inclusion but ran out of time
  • Setting up IPFS and Robonomics incorporating all the blockchain functions, methods, endpoints, requests, and responses from the Robonomics documentation.

Go-to-Market

Technology advancements for smart environments of the future have helped us as a society grow more and more connected for seniors aged 65+. Seniors represent 5% of population yet 42% of the $3.8 trillion healthcare industry. For information encompasses IoT technologies which include data, software, and hardware, the market is around $520 billion. As medical investments scale, they will make remote healthcare more accessible for everyone.

Medbot's go-to-market strategy is Robots-As-A-Service being offered to seniors and healthcare professionals through a monthly subscription based model. The healthcare market includes health and wellness, home care, residential care, medical care. Individual members (seniors), family/friend caregivers, or personal care workers will be able to purchase the product. Stakeholders include manufacturers, medical distributers, group purchasing organizations, big pharma like pharmacies and drugmakers, and healthcare organizations like senior homes, speciality clinics, and hospitals.

  • Request medical robot services with mobile application
  • Service cloud connection
  • Dispatches and monitors robots

The AI-powered blockchain technology means that it will get more powerful with user generated medial content in a peer to peer network. Enable medical robots to launch based on payment with our robots-as-a-service model. Medbot can be seen as a communication layer via arduinos that dispatches the robots when the customer pays. It merges the technical information in ROS that makes the medical robot move and financing information into a single instrument. While all the infrastructure that enables this to happen is fully distributed, cannot be censored or controlled by any single entity. This builds trust among the healthcare services, provide direct medical access via dapp connected to decentrailized sensor networks. Considerations regarding cybersecurity, coexistence, compliance, connectivity, and cloud with code efficiency were made as the number of users scales.

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