Baby FM is AI temperature monitoring system

Baby FM can play a significant role in the treatment and management of rare diseases. By enabling early detection, monitoring treatment efficacy, tracking disease progression, facilitating remote patient monitoring, and contributing to research efforts.

1. Early Detection of Fever-Related Symptoms: Many rare diseases are associated with fever or abnormal temperature fluctuations. BABYFM's AI algorithms and ML models can help identify subtle temperature changes or patterns that might indicate the onset of fever-related symptoms associated with specific rare diseases. Early detection can allow for prompt medical intervention and improved management of symptoms.  

2. BABYFM's continuous temperature monitoring can help track the effectiveness of treatments for rare diseases. By analyzing temperature trends over time, the system can provide insights into the response to different therapies, medications, or interventions. This information can assist healthcare professionals in adjusting treatment plans and optimizing patient care.

3. By providing continuous monitoring and alerting of temperature deviations, BabyFM can help reduce unnecessary medical procedures, testing, and duplicative travel. This can result in cost savings for patients and caregivers by minimizing expenses associated with repeated visits, tests, and consultations.

4. BabyFM's telehealth consultation and scheduling features offer convenience and accessibility to healthcare professionals. Patients and caregivers can remotely connect with medical experts, reducing the need for frequent in-person visits. This convenience can save time, effort, and resources, particularly for individuals with rare diseases who may require frequent monitoring and follow-up.

5.  The AI analysis and ML models integrated into BabyFM can provide valuable insights into treatment efficacy, disease progression, and response to therapies. This information can help healthcare professionals optimize treatment plans, personalize care, and improve patient outcomes, thereby positively impacting the lives of individuals with rare diseases.

6. BABYFM's telehealth consultation and scheduling features can be particularly useful for patients with rare diseases who may require frequent monitoring and follow-up. With remote access to temperature data and the ability to communicate with healthcare professionals through the system, patients and their caregivers can receive timely guidance, support, and medical advice without the need for frequent in-person visits.

7. BABYFM's data collection capabilities and analytics can contribute to research efforts related to rare diseases. Aggregated and anonymized temperature data from multiple patients can provide valuable insights into disease patterns, progression, and treatment responses. Such data can facilitate collaboration among researchers, clinicians, and pharmaceutical companies, potentially leading to advancements in understanding and treating rare diseases.

8. BabyFM's telehealth consultation and scheduling features offer convenience and accessibility to healthcare professionals. Patients and caregivers can remotely connect with medical experts, reducing the need for frequent in-person visits. This convenience can save time, effort, and resources, particularly for individuals with rare diseases who may require frequent monitoring and follow-up.

9. The AI analysis and ML models integrated into BabyFM can provide valuable insights into treatment efficacy, disease progression, and response to therapies. This information can help healthcare professionals optimize treatment plans, personalize care, and improve patient outcomes, thereby positively impacting the lives of individuals with rare diseases.

BABYFM, a sensor-data-AI-based continuous temperature monitoring system, offers alarm, notification, and reporting features for home and hospital environments. As the first of its kind on the market, it helps parents and patients track metabolic responses through CFM and sends analytics to doctors for improved productivity, management, and digitized patient records. 

BABYFM's AI analyzes real-time temperature data, identifies patterns and trends, and alerts users and healthcare professionals of potential health risks. The AI algorithm is trained on temperature readings to detect deviations from normal ranges and alert of potential issues. 

With ML models, BABYFM enhances data collection and analysis, leading to earlier detection of health problems and improved patient care. The system includes a contact sensor, a smart battery, and data collection via cellular and Bluetooth. Chatbot and telehealth consultation and scheduling are also available. The AI can distinguish viral from bacterial infections based on temperature trends and analyze other vital signs for improved accuracy.

BabyFM addresses the specific needs of individuals with rare diseases by enabling early symptom detection, monitoring disease progression, providing remote monitoring and support, facilitating personalized treatment optimization, and contributing to research efforts. These features cater to the unique challenges and requirements faced by individuals living with rare diseases.

Temperature trend analysis, including changes in basal temperature, can help track the progression of rare diseases. By observing temperature patterns, healthcare professionals can assess the rate of disease progression, identify exacerbations or remissions, and adjust treatment plans accordingly. This monitoring enables proactive management of the disease and helps in preventing or minimizing complications. Basal temperature measurement and temperature trend analysis can be used to evaluate the effectiveness of treatments for rare diseases. Changes in temperature patterns can provide insights into how the body is responding to specific therapies. If treatment is successful, there may be a stabilization or normalization of temperature trends. In contrast, worsening or fluctuating temperature trends might indicate the need for treatment adjustments or alternative approaches (by monitoring basal temperature, healthcare professionals can gain insights into hormonal health, fertility, and certain metabolic conditions).

By providing continuous temperature monitoring and early detection of fever-related symptoms, BABYFM can potentially reduce the time, cost, resources, and unnecessary travel and testing for patients and caregivers. 

By understanding the individual's temperature patterns, treatment plans can be tailored to their specific needs, optimizing symptom management and improving their overall quality of life.

Our team was fully engaged during the beginning of the Covid19 pandemic in the Republic of Serbia to invent solutions that will improve the conditions of the health workers at the front. We have developed the solution Doctors for Doctors, for monitoring the physical and mental health of the doctors during the pandemic and offering the right help in critical situations. The project was supported by the Serbian Government and the Ministry of Innovation and technological development of Serbia. At the same time, team members and co-founders of Baby FM Dr Ivan Soldatovic and Vladimir Jeftovic were engaged in the development of the world's first bracelet for covid prediction AVA (Switzerland). Ivan Soldatovic is a consultant for international companies for clinical trial designs (Roche, Phizer, LaRosche Possay, CoreMedic, etc) and a professor at the Faculty of Medicine. Vladimir Jeftovic is a former employee at Amazon, who was engaged in Alexa voice recognition system development, and CEO at DIVS technology focused on neurological triage in diabetes treatment. CEO and co-founder Tamara Papic was engaged in business development for several international companies, and experienced in project management, innovative ecosystem development, etc. The team member prof. Dr. Nenad Jovičić was engaged in international and national IoT solution development and design of custom electronics, as well as Milijan Ćelić who is the team lead for software development was engaged in several projects for USAID, and EBRD, creating the solutions which transfer the knowledge from innovative systems to the industry in Bosnia and Hercegovina. Our team is working and creating solutions from the Balkan area (low- and middle-income countries) and understands the challenges which could be applicable in all other areas around the globe. 

We are willing to serve and solve the biggest challenges with advanced technologies and our knowledge. 

Tamara Papic is a member of the Health tech cluster in Serbia, formed by the Serbian government and USAID project Serbia Innovates. She is experienced in sensor technologies and multidisciplinary work with children with dyslexia. She has established a strong partner network for Baby FM with Institutes for cardiovascular diseases, Child hospitals, and private hospital chains in Serbia Aci Badem Bel Medic, Biocell Hospital, and Vincula Biotech group.

1. Sensor Data AI-Based Monitoring: Baby FM utilizes sensor data and AI algorithms to continuously monitor the temperature. This real-time monitoring and analysis provide valuable insights and early detection of potential health risks. The integration of AI technology enhances the accuracy and efficiency of temperature analysis, contributing to improved patient care and outcomes.

Continuous Monitoring and Trend Analysis: Unlike traditional intermittent temperature measurements, Baby FM offers continuous temperature monitoring. This continuous monitoring allows for the detection of subtle temperature changes and the identification of temperature trends over time. By analyzing temperature trends, the solution can provide early indications of health issues, enabling proactive intervention and management.

Remote Access and Telehealth Consultation: Baby FM incorporates telehealth consultation and scheduling features, enabling remote access to healthcare professionals. This remote access eliminates the need for frequent in-person visits, reducing travel, costs, and unnecessary resource consumption. Remote consultations also offer convenience and accessibility for individuals with rare diseases, enhancing patient experiences and reducing the overall environmental impact.

Data-Driven Insights and Research Contribution: Baby FM collects and analyzes temperature data, contributing to valuable research insights. Aggregated and anonymized data from multiple users can aid in understanding rare diseases, treatment responses, and disease patterns. This research contribution facilitates advancements in medical knowledge and enhances the development of more effective treatments and interventions.

Reduction of Resource Consumption: Baby FM's continuous monitoring eliminates the need for frequent disposable temperature measurement devices, reducing single-use product consumption. By minimizing unnecessary plastics and medical waste, the solution promotes sustainability and environmentally friendly practices within the healthcare sector.

Optimization of Healthcare Processes: Baby FM optimizes healthcare processes by enhancing data collection, analysis, and reporting. The AI algorithms and ML models integrated into the solution facilitate earlier detection of health problems, improved diagnostic accuracy, and personalized treatment plans. These optimizations lead to more efficient healthcare delivery, reduced costs, and minimized resource utilization.

Alternative Packaging and Transportation Optimization: Baby FM's focus on sustainability extends beyond temperature monitoring. The solution aims to create and promote alternative packaging that is reusable, recyclable, or biodegradable, without compromising sterility or safety. Additionally, by addressing shipping inefficiencies, cold storage requirements, and last-mile delivery challenges, Baby FM helps optimize the transportation of supplies and treatments, reducing energy consumption and environmental impact.

1. Adoption and Market Penetration: Increase the adoption of Baby FM in both home and hospital environments, expanding its user base and market presence. This could involve strategic partnerships, marketing campaigns, and targeted outreach to healthcare providers and parents.

2. Improved Diagnostic Journey: Enhance the diagnostic journey for individuals with rare diseases by reducing the time, cost, and duplication of travel and testing. Baby FM can aim to streamline the diagnostic process, provide earlier detection of health risks, and improve the overall experience for patients and caregivers.

3. Clinical Trial Support: Collaborate with research institutions and pharmaceutical companies to leverage Baby FM's data collection and analysis capabilities for supporting clinical trials and research efforts. By providing valuable insights and contributing to research advancements, Baby FM can play a role in accelerating the development of treatments and interventions for rare diseases.

4. Research Collaboration and Data Sharing: Foster collaborations with research institutions, advocacy groups, and rare disease communities to promote data sharing and contribute to scientific knowledge. By actively engaging in research initiatives, Baby FM can contribute to advancing the understanding and treatment of rare diseases.

5. Integration with Healthcare Systems: Collaborate with healthcare systems and electronic medical record (EMR) providers to seamlessly integrate Baby FM's data and analytics into existing healthcare infrastructure. This integration can enhance care coordination, facilitate remote monitoring, and support better communication between patients, caregivers, and healthcare professionals.

6. Sustainability Initiatives: Strengthen the sustainability aspect of Baby FM by focusing on eco-friendly packaging, reducing waste, and optimizing the product's environmental footprint. Emphasize sustainable manufacturing practices, alternative materials, and transportation optimization to align with global sustainability goals.

1. Adoption Rate: Track the number of Baby FM units deployed and the rate of adoption among the target user base, including both home users and healthcare institutions. This metric reflects the market penetration and acceptance of the solution.

2. User Engagement: Monitor user engagement metrics, such as frequency of temperature readings, duration of usage, and user feedback. This provides insights into the level of user satisfaction, adherence to monitoring protocols, and overall user experience.

3. Diagnostic Journey Improvement: Assess the reduction in time, cost, and duplication of travel and testing for patients and caregivers. This can be measured through surveys, interviews, or data analysis, comparing the diagnostic journey before and after using Baby FM.

4. Clinical Trial and Research Collaboration: Evaluate the number of collaborations with research institutions, participation in clinical trials, and research publications or contributions made using Baby FM data. This metric reflects the level of engagement and impact of Baby FM in advancing research and treatment options for rare diseases.

5. Patient Outcomes: Monitor patient outcomes, such as symptom management, disease progression, and treatment effectiveness. This can be assessed through medical records, patient surveys, or follow-up consultations. Improvement in patient outcomes indicates the efficacy of Baby FM in enhancing the care and management of rare diseases.

6. Sustainability Measures: Track sustainability initiatives implemented by Baby FM, such as reduction in single-use product consumption, waste management practices, and adoption of eco-friendly packaging. These metrics reflect the commitment to sustainability and the environmental impact of the solution.

7. Integration with Healthcare Systems: Measure the integration and interoperability of Baby FM with existing healthcare systems and electronic medical record (EMR) platforms. This includes the seamless flow of data, integration with telehealth platforms, and ease of access for healthcare professionals. Increased integration indicates progress towards optimizing healthcare processes and enhancing care coordination.

1. Early Detection and Timely Intervention: Baby FM's continuous temperature monitoring and analysis can help detect early signs of symptoms or abnormalities associated with rare diseases. Early detection allows for timely medical intervention, leading to improved outcomes and effective management of the condition.

2. Personalized Care and Treatment Optimization: By analyzing temperature trends and basal temperature, Baby FM enables healthcare professionals to provide personalized care and optimize treatment plans. This individualized approach helps tailor therapies to the specific needs of each patient with a rare disease, enhancing symptom management and overall well-being.

3. Reduced Diagnostic Burden and Healthcare Costs: Baby FM reduces the burden of frequent travel and testing for individuals with rare diseases. Providing continuous temperature monitoring and analysis, it minimizes the need for duplicative diagnostic procedures, reducing costs and resource utilization while improving the diagnostic journey for patients and caregivers.

4. Remote Monitoring and Telehealth Consultation: Baby FM's integration with telehealth consultation and scheduling enables remote access to healthcare professionals. This remote monitoring capability allows individuals with rare diseases to receive regular care, guidance, and support without the need for frequent in-person visits. It improves accessibility, reduces travel-related challenges, and ensures timely medical attention.

5. Research Advancements and Collaboration: Aggregated and anonymized temperature data collected by Baby FM can contribute to research efforts in rare diseases. By sharing data with research institutions, Baby FM can support the development of a deeper understanding of rare diseases, potential biomarkers, and treatment responses. This collaboration can accelerate research advancements and drive progress in the field.

6. Improved Quality of Life: By enabling early detection, personalized care, remote monitoring, and optimized treatments, Baby FM can significantly improve the quality of life for individuals with rare diseases. It empowers patients and caregivers with valuable insights, enhances disease management, and provides reassurance and support through continuous monitoring and access to healthcare professionals.

By introducing AI into CFM, we have the first movers’ advantage on the market. BabyFM incorporates key-enabling methodology and technology, by combining highly sustainable and reusable hardware (wearable IoT) that continuously measures temperature with mobile and web apps with incorporated AI and ML algorithms that analyze received data in real time.

Our  AIoT-based system includes alarms, temperature trends, medication dosages, notifications, and telehealth support with the prediction of the symptoms, where such data can be used as part of early diagnosis and recovery prediction, rather than just for temperature measurement. To achieve this, a combination of hardware and software was required, where
the hardware part of BabyFM includes:
• contact sensor in a casing made from food-safe material, for temperature measurement 
• smart battery – that can be used for over 12 months in average usage without charge and where the unit is initially activated by a specific motion and turned off by the user when no longer needed. The battery lifecycle has its own firmware for sleep and wake-up conditions, as well as for frequency of data transferring or saving.
• Bluetooth module for the data collection on mobile devices and 
• Memory -that allows for creating accurate data, even if the Bluetooth connection is lost, or the Bluetooth device is out-of-range. 
• PCB board – controlling the unit.
• Adjustable band, that holds both a temperature sensor and unit firmly in the desired position, which replaces the need for adhesive pads, but also ensures for the wide use-case

project manager

two developers

two hardware engineers

designer

CSO

two business development

AI engineer

Three years.

We are incorporating diversity, equity, and inclusivity into our work every day.

1. B2C. Working parents with babies/small children–42M with children under 6 in the EU (Eurostat), who must choose between remaining awake with their kid and going to work. 
With bought device and basic, free subscription, we are offering them: 
a) More sustainable (we remove the need to buy additional adhesive single-use pads) and
b) accurate (adhesive pads can drop off by sweating) and 
c) cheaper solution-During 2 years,re-usable BabyFM costs €69 compared to 
€40-90(unit)+120(single-use pads).
d) adjustable sensor band (for different ages) 

With a premium subscription, we'll provide AI-based functionalities, for €9.99/per device monitored/per month

2. B2B. Clinics/hospitals -firstly pediatrics (18K+ offices in EU) and recovery, later other procedures. With a rapidly aging population and COVID, a number of procedures &longer recovery is growing with a CAGR of 2022-27 of 3.51% and a market size of €1.08Tn(Statista).
To segment we will offer all AI advanced functionalities (see 2.2&5.1)+ability to monitor 100+ devices via d

We will market BabyFM to clients as locally as a smart thermometer with a wellness app.  In this stage, we will promote directly to consumers through our web shop (B2C) locally using paid social media ads, SEO, user stories, clinical trial findings, and influencer marketing.

We will encourage pediatricians/clinics to rent their BabyFM units to parents, and patients practically using them as distributors (B2B2C), where we intend to position ourselves as a next-gen solution in CFM.

In 1st stage, we will market BabyFM directly to consumers(B2C)with €40 one-time payment for hardware and basic subscription locally, where, after we receive EMA approval, we intend to increase EUprice to the current average competitor price of €69 and introduce €9.99/month/child premium, AI-based features, simplified for parents. Since most parents are very curious about their baby/child's illness and have several children, with this approach we ensure an initial LTV of €250/user. 
To increase retention and LTV, after illness is over, we intend to introduce features that transform BabyFM into a parent companion in a healthy child lifestyle, where we will offer tips and practices from pediatricians, with regard to the physical condition of the child and previous data collected, where we expect to raise LTV to avg €320/user. 
To clinics/hospitals, we intend to offer a more robust solution for €320 in 2nd stage, with multi-patient subscriptions (B2B), ranging €10-€39/patient/month, depending on features, where we expect LTV ranging in average between €3.220(5/patients, low-tier subscription)- €14.360(10/patients, high-tier subscription), based on a 3-year average usage.  
We will strongly encourage pediatricians to include the rent of BabyFM to parents during illness, with a revenue-sharing proposition. This approach was already interesting to several clinics, where we can use them as distributors, more present in parents' lives as trusted sources, compared to pharmacies, with much lower operating costs.

We already started Stage 1 clinical trials with several institutions, as described. We plan to use clinical trial data as a form of success stories material for approaching other medical institutions and parents, which will allow us to make local traction in the near future.  

Because of that, we plan to offer BabyFM's first €40 version and make income in mid-2023. (from pre-orders). We expect to sell 560 of those versions locally in the first year to generate income for the EMA approval submission fee (€20K) and small business discount. Since EMA prioritizes innovative pediatric technologies, we can enter PRIME: priority medicines program, where participants can gain EMA accelerated priority approval and 80-100% off fees, which will greatly speed up EU market entry (forecast for 2024).
Once EU approved, we will firstly employ B2C and B2B2C(pharmacies, online stores) approach, later introduce the B2B approach (pediatricians, clinics, hospitals)where we plan to sell 5.400 Baby FM and 680 NeoFM systems and 3.300 additional subscriptions in 2024(projection below), where to expect to break-even during Q3/year2. 
During the first two years, we will reinvest a large portion of revenue in marketing and platform improvement to establish BabyFM as the next-generation CFM, maintaining a user base, reducing churn, and introducing new revenue streams. Later, we will start accumulating profit larger percentage(see below). We expect a 75% profit margin from direct sales for both systems, which gives us space to approve discounts to re-sellers and to re-invest in marketing and improvements. When we deploy the B2B2C model, that margin will be lowered to 45%,(30% on average is going to the distributor channel), the same time resulting in much higher sales volume.