Taking healthcare beyond with autonomous mobile clinics

Highlights

United Nations Sustainable Development Goal 3 proposes a universal health goal by 2030.
Autonomous Mobile Clinic (AMC) is an innovative technological solution that can address this requirement, enable the outreach of healthcare to places where it is difficult to reach.

When we build automation toward humanitarian causes, it can sustainably yield positive results. At least half of the world's population does not have access to essential healthcare services ^[1]. For the Least Developed Countries (LDCs), basic healthcare is difficult to obtain. LDCs spend less than 5% of their GDPs on healthcare ^[2].

To address this issue, the United Nations Sustainable Development Goal 3 proposes a universal health goal by 2030. It calls for widespread efforts to "Ensure healthy lives and promote well-being for all, at all ages."[3]. As LDCs lack financial resources, they would require cost-effective solutions to help them work towards this goal and succeed sustainably.

Understanding the how

Autonomous Mobile Clinics: smart AI for health

Autonomous Mobile Clinic (AMC) is an innovative technological solution that can address this requirement. This comprises autonomous vehicles that can enable the outreach of healthcare to places where it is difficult to reach. These vehicles can also help people with disabilities or challenges with mobility who cannot visit a public healthcare institution alone. These clinics also include smart AI-based technologies to offer effective treatments and testing options for common illnesses and symptoms or recommend further investigations through telemedicine systems.

Benefits of Autonomous Mobile Clinics

Enabling preventive healthcare practices for the long term

There are numerous benefits of Autonomous Mobile Clinics. These can not only address the current lack of essential healthcare access for isolated groups of residents but can also help the healthcare providers be future-ready and enable preventive healthcare practices for the long term.

AI doctors can minimize healthcare expenses: AI doctors are devices which can be trained with large amounts of health data securely and used to provide healthcare to patients efficiently, with minimal human efforts. AI doctors can take the patients through a simple set of questions, scan their health vitals and rapidly come up with results and consultations. AI doctors, coupled with human experts, can solve the most complex health challenges in LDCs. These AI doctors can perform screening activities and diagnostic tasks as part of primary care so that doctors can focus on the complexities.
Smart apps can enable the monitoring of health data: With minimal connectivity, providing healthcare in remote regions can be a challenge. However, having apps that can collect and monitor health data and store them through innovative caching systems can help AMCs provide data insights despite internet issues. The AMCs can travel back to a relatively-connected region and sync the collected data to centralized systems so that any healthcare provider across the globe can analyze the data and recommend treatment. This way, AMCs eliminate the need for expensive setups that can be a roadblock to healthcare improvements in LDCs.
Automatic sanitization systems can create a mobile hospital-like environment: For AMCs to succeed in LDCs, patients must be treated in a safe, hygienic environment. This mitigates the risk of secondary infection and transmission of communicable diseases by healthcare providers. The COVID-19 pandemic has seen progress in automated sanitization systems, which are portable and compact enough to fit inside the automated mobile clinic. These devices are easy to use and don't cost much to maintain, thus keeping the operational costs running low. These devices also help manage the containment of medical waste and storage of test samples, again with minimal human intervention.
Digital modules that can connect to healthcare knowledge centres to increase health awareness: A natural progression would be to bring the people of remote and isolated regions up to speed with the latest knowledge to create awareness and help people understand how to stay healthy through good food and hygiene practices. Doctors working full-time in these remote locations would also need access to updated reference resources which can help them improve their treatment and diagnosis techniques. AMCs can serve as a platform that connects healthcare knowledge centers across the globe to the remote regions of LDCs and provide seamless knowledge transfer. This would improve the recency and relevance of healthcare, especially for countries that are still coping with preventable diseases.

The primary focus of Autonomous Mobile Clinics is to provide healthcare efficiently at the touch of a button.

The way ahead

Unhindered, accessible and affordable healthcare

We can achieve universal health coverage with a roadmap that employs technology to help people in immediate need and then, over time, help manage healthcare needs such that preventive healthcare can reach any region on the planet. Lack of financial resources should not hinder basic healthcare access. The plan should be to use innovations like Autonomous Mobile Clinics to save money while capitalizing on technological advancements to make healthcare accessible and affordable for those in need.

Buffer overflows: It limits the effectiveness of zero-day memory corruption vulnerabilities. Modern operating systems such as macOS, Windows Vista, Linux, Solaris, Unix, and Unix-like environments feature these protection mechanisms. Desktop and server protection software can also mitigate zero-day buffer overflow vulnerabilities. Heuristic termination analysis is usually used in these technologies to prevent attacks before they can cause any damage.
In-depth system monitoring: Companies need to monitor as many events as possible to detect modern zero-day attacks, which include all network traffic, all hidden system processes, all existing hooks, all floating code, and so on. A behavior analysis algorithm can effectively process events in streams rather than individually. It detects and records the relationships between different sets of acquired data. However, it demands a lot of time and effort.
Baseline with behavior analysis: In behavior analysis algorithms, all monitored data and any previously recorded data are further analyzed in real-time to establish a baseline of normal behavior. Behavioral analysis algorithms must be able to analyze all future events as a unified stream instead of treating them individually to predict future events. A larger dataset can establish a more accurate baseline, which, in turn, allows to detect deviations from the stated baseline with greater accuracy. This also enables the creation of a baseline that includes both malware and non-malware attacks, which is time-consuming and expensive.
Web Application Firewall (WAF): It is intended to be the fastest method to filter out malicious traffic and prevent vulnerabilities from being exploited. Zero-day attacks are a major problem for security. Flaws must be found, patched, and made safe, but web traffic can still target vulnerabilities. To stay updated, WAF must be able to act in real-time and keep adapting.

A program that would offer a monetary reward to security researchers who choose to responsibly disclose vulnerabilities instead of selling the information to the highest bidder could potentially solve this problem. By working together and sharing the information they discover with software vendors, security researchers can help to combat the threat of hackers before they have a chance to exploit the vulnerabilities. Companies should apply patches as soon as possible to reduce the exposure window for any given vulnerability.

The detection of previously unknown software vulnerabilities can be accomplished through several strategies.