Mobile Vaccine Monitor (Intel IoT)

Project overview:
Often this is applicable to under developed (N.Africa) and developing nations (like India) where the vaccines storage environment (temperature) tracking is a big problem. When the environment is not optimal(temperature is not within the expected range), the efficacy of these vaccines is lost. All the health worker carries is a portable box with some cold pads (door to door polio vaccine campaign). Our connected maraca has to help ensure the safety and efficacy of the vaccines. While the traveling health workers go around, based on the vaccine type and recommended environment setting, sensor data will be sent to the cloud.

Over the cloud using data analytics we can predict if a vaccine vial is about to get spoiled (predictive analysis), so that it can be moved to a safety spot on time. Also, the data will help us determine if a health worker has not followed the best practices, and take actions accordingly. Also, using smartphones and cloud, health workers can be prevented to administer spoiled vaccine. This idea can be extended to efficient storage and handling of other environment-sensitive medicines as well.

The unique and innovative attributes of your Project:

At present the commercially popular solution is to only monitor the cold chains (statically installed freezers) to ensure proper storage of the vaccines. But the health workers need to go around on the field most of the time to administer the vaccines. Our application offers a solution to monitor the storage and safe keeping of the vaccines on the move. The recorded data also serves as a very important input for the scientists and engineers working on creating more environment-robust insulation box and vials. Our solution is economic as well. In case, the health workers need to go to remote areas, where Internet connectivity is absent, all the recorded data can be stored in the IoT device, to be pushed to the cloud in a batch, once the worker is back to connected area. Also, in the absence of Internet, anomaly detection algorithm running in the kit, can give a forewarning to the health worker immediately by turning on the buzzer.

What is the target audience and available market for your Project?

Target Audience: Health workers administering vaccines on outdoor fields.

Available Market: Health Organizations, Government Offices, who are investing a fortune every year to vaccinate kids in the country. This is more applicable to developing countries, where at present, availability of high quality insulated portable boxes, fast and efficient travel means to different areas is a challenge.

How does your Project technically work?

Intel Galileo board with multiple sensors (temperature, light, air quality, gyro) attached to it, is running in a portable box with vaccines, which a health worker is carrying. The board can be connected directly to WiFi, or we can enable to Bluetooth to connect to the mobile phone of the worker. Sensor data recorded is processed in an anomaly detection algorithm inside the IoT board and if it detects environment anomaly, the buzzer starts sounding. The processed data is also periodically pushed to the cloud for further analysis. Analyzed data will send a live Push Notification to the mobile phone of the health worker, and his coordinator (a meaningful and informative message is displayed) to handle the crisis situation effectively.

How does your Project take advantage of

a. Cloud connectivity?

Crucial sensor data recorded inside the portable box is periodically pushed to the cloud. Cloud has enough resource to efficiently process the huge amount of data received. The data analysis done on cloud, is not possible to do in the IoT board. The insights received from the data analysis not only helps a health worker take corrective measures on time, but also promises the building of a better solution in the future.

b. Sensor utilization?

Multiple sensors are used to monitor the environment of the portable box carrying the vaccines. In the future GPS sensors can also be added to track the movement of the health worker, generating more insights. The amount of information gathered from the sensors in an absolutely non-intrusive way is very effective in such ground level scenarios.

Usage of each sensor data: .i. Temperature==strict temperature range should be maintained, otherwise raise alert .ii. Light==Over exposure to light can spoil the vials, raise alert .iii. Air Quality==degradation in air quality means, insulation is not working properly, raise alert .iv. Gyro==if the vial is not kept in a proper position and if it is moving too much, it can go bad, raise alert .v. Buzzer==raise alert

How does your Project make use of

a. Software components?

Components used: 1. Intel XDK for IoT to write JavaScript programs to run on Galileo 2. Putty to run setup commands and install npm modules on Galileo 3. Android SDK to write Android App to receive Push Notifications from the Cloud 3. Java to write Restful web services to receive data from Galileo 4. Linux programming on Amazon EC2 to setup Amazon cloud for data analysis 5. Apache Tomcat to run Restful web services to receive data from Galileo 6. Elastic search algorithm in Java setup to do data analysis for huge amount of data 7. NoSQL database setup to store the received data 8. HTML5 CSS programming to setup Kibana dashboard displaying real-time processed data with intuitive details 9. Java program to enable real time Push Notification to Android Phones using Amazon SNS and Google Cloud Messaging Service (GCM) 10. OS used: Windows 8, Linux. 11. We have done a full setup of Intel Analytics Cloud as well, but since the connectivity was intermittent, we moved to AWS.

b. Hardware components?

1. Intel Galileo board 2.Grove kit and sensors (temperature, light, air quality, gyro) 3. WiFi card

c. The Dev Kit?

All the hardware components listed above came in the Dev Kit

Future Work:

a. Connect the Galileo board directly to the phone using Bluetooth. In remote areas, where Internet connectivity is absent, the data from the sensors will be stored inside the phone's SD card over Bluetooth. Also, the data can be stored inside the IoT board itself. Later when the health worker is in Internet zone, the data will be pushed to the cloud.

b. An Android app for the health worker: Each health worker gets money for administering a vaccine. This is one of his biggest incentive. After administering the vaccine, he will be using the app to register the administration. These registrations will be used to calculate his incentive. As soon as the IoT board detects a vaccine going bad, it will disable the registration of administering of that vaccine. This way, the health worker won't administer a spoiled vaccine, just for incentive.

c. One box can be made to carry different kinds of vaccine vials to reduce luggage. Each type of vaccine has a different set of optimal environmental thresholds. The IoT kit should be able to monitor each of the different vaccine vials, based on their different set of optimal thresholds, and not using one common set of thresholds for all the vials in the box.

Our Learning:

a. Intel Galileo board is way more reliable, powerful and easy to program with compared to Raspberry Pi.

b. Using JavaScript in Intel XDK for IoT is really amazing. We are working with five different sensors, a buzzer, making rest calls to the cloud -- all are done with less than 110 lines of codes! Learning curve is steep, but once you are familiar with the system and the libraries, running a fully working app on the Galileo board is really quick and easy.

b. Spark Core seems more compact than Galileo board. We have heard Intel Edison board is at par with Spark Core, but we haven't worked with it yet.

c. Uploading programs to Galileo board over WiFi is not very reliable when many people are sharing the WiFi and pairing up their laptops with the Galileo board. Hence, we had to use the Ethernet cable to upload the code to Galileo. But, once code started running, the board was working fine and efficiently over the WiFi.

d. Sometimes, the board becomes unresponsive, and we had to reboot it and restart our app. As per our experience, it is the same with all the boards we have worked with. These boards need sometimes before the app execution is stabilized. We hope if proper logging can be done, this issue can be addressed more effectively.

e. The sensor value reading by Galileo board and data push over the WiFi card is very fast. Really useful for hard real time critical applications.

f. We had done a full setup of the sensor recorded data on Intel Analytics Cloud as well. But since the connectivity was intermittent, we moved to AWS.

What more we would like to know about the Intel IoT Kit:

a. What kind of battery backup it needs, and how long on an average it can run continuously on battery. This is an important factor to determine what are the apps it is suitable for.

b. How reliably the Intel IoT kit can withstand extreme environment conditions?

c. Performance benchmark

d. Fault tolerance features

e. Can we add addition flash storage to it?

f. What all computer peripherals (other than Ethernet, power cable) we can attach?

 
 

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