Secure, time&energy-aware IoT with a UAV

I provide a three-tier solution with UAV-assisted robotic monitoring IoT system for scalable and verifiable (secure, transparent and immutable by blockchain with AI) monitoring and data collection to track ecosystem conditions.

It will help especially the people in poor and developing countries have resilient ecosystems. Therefore, my three-tier solution can affect the lives of hundreds of millions or perhaps billions of people in a global scale especially when you consider African countries and southeast Asia countries like China and India.

For resilient ecosystems, we need to monitor the ecosystems fast&securely and show the required real-time reactions against anomalies in case anomalies are detected.

By proposing a UAV-Assisted clustered-robotic monitoring system, we aim to collect data from the environment in a secure, time-aware, energy-aware and efficiency-aware way. For this purpose, we should solve the following three subproblems.

In the first tier, each cluster member (CM) robot needs to collect data from surrounding sensors in a time-aware and energy-aware way. For this purpose, it needs scalable scheduling (data collection) algorithms.

In the second tier, each cluster head (CH) robot needs to collect data from  CM robots in a secure, transparent and time-aware way. For this purpose, it needs blockchain protocols whereby the data can be stored securely and shared transparently among all CM robots in the cluster, which increases the resilience of the system against malicious attacks in the IoT era. It is also required for CH election among robots.

In the third tier, a UAV with a limited-capacity battery needs to collect data from the CH robots in an efficiency-aware and energy-aware way. For this purpose, it needs not only energy-aware but also efficiency-aware routing algorithms coupled with trajectory optimization algorithms.

We propose a 3-tier solution via a UAV-assisted robotic monitoring IoT system that consists of a UAV, robot clusters, and sensor clusters.

In the first tier, each cluster member (CM) robot collects environmental data from sensors by using Uniforming Random Ordered Policy (UROP). Here, UROP uses no feedback to learn battery and buffer states of sensors. Thus, it is a time-aware&energy-aware data collection policy by reducing communications overheads.

In the second tier, a cluster head (CH) robot collects data from cluster member (CM) robots by blockchain supported with AI. Here, blockchain provides data transparency&security. Thus, the collected and evaluated data can be shared among the robots, which helps robots elect new cluster head easier unless the current CH robot performs well and has sufficient energy.

In the third tier, a UAV with a limited-capacity battery collects data from CH robots by visiting an optimal portion of them depending on its battery capacity. Here, we aim to minimize total joint cost of energy consumption and data efficiencies of CH robots by visiting the optimal set of CH robots via Efficiency&Energy-Aware Data Collection Strategy (EEADCS).

Hence, the proposed robotic monitoring system collects data from the environment in a secure, time-aware, energy-aware&efficiency-aware way.

Our target population is people especially in rural areas of low-income or developing countries. Especially because of bad economies in these countries, companies may look for ways of not using costly filters that can industrial wastes from mixing the soil or water. Not using these filters sometimes causes severe environmental problems, which causes economic and psychological problems. 

As an example from Turkey in the last two months, the Marmara Sea suffers from mucilage which is caused by industrial wastes mixing directly into the sea for the last two to three decades. This mucilage in fact kills the sea by harming biodiversity and biological life in the Marmara Sea. The negative consequences are not only biological and economic but also psychological and cultural. While people watch the blue Marmara Sea to become more relaxed for decades, they watch its illness appearing with mucilage to go towards its death for two months. 

As a person living and loving the Marmara Sea in Turkey for three decades, I am unfortunately among such underserved people for the last two months because of this mucilage. Therefore, I can understand the needs of such underserved people, and I benefit from this unfortunate experience as I develop my solution.

To overcome such problems, we need scalable and verifiable monitoring and data collection to track ecosystem conditions, such as biodiversity, carbon stocks, or productivity. If we use such a monitoring and data collection system, then we can detect such environmental problems at their initial phase and take necessary precautions to avoid the later stages of environmental problems like mucilage.

To solve this problem of resilient ecosystems, I provide a UAV-assisted robotic monitoring IoT system for scalable and verifiable (secure, transparent and immutable by blockchain with AI) monitoring and data collection to track ecosystem conditions, such as biodiversity, carbon stocks, or productivity.

To overcome the environmental problems and take the necessary precautions, we need scalable and verifiable monitoring and data collection to track ecosystem conditions, such as biodiversity, carbon stocks, or productivity. If we use such a monitoring and data collection system, then we can detect such environmental problems at their initial phase and take necessary precautions to avoid the later stages of environmental problems like mucilage.

To solve this problem of resilient ecosystems, I provide a UAV-assisted robotic monitoring IoT system for scalable and verifiable (secure, transparent and immutable by blockchain with AI) monitoring and data collection to track ecosystem conditions.

I chose the 'prototype' stage because some parts of this solution has already been published publicly, presented publicly, and awarded.

In the first tier of my solution, I applied Uniforming Random Ordered Policy (UROP) whereby I have published several papers and received third place in the global best (graduate) student paper award by IEEE Computer Society. This shows the strength of the algorithm, UROP.

In the third tier of my solution, I applied Efficiency&Energy-Aware Data Collection Strategy (EEADCS) whereby I have published papers and receive third place in the poster competition with the theme of solutions in post-Covid-19 era by IEEE Rising Stars Conference. This shows strength of the algorithm, EEADCS.

In the second tier of my solution, I applied a lightweight blockchain protocol and working on it to improve its scalability and security by using AI.

I am looking forward to your support for later stages starting at pilot.

In the first tier and the third tier of my proposed 3-tier solution, I use completely novel and robust algorithms which have already been awarded by the Institute of Electrical and Electronics Engineers (IEEE) and IEEE Computer Society.

In the first tier, I apply my novel data collection algorithm, Uniforming Random Ordered Policy (UROP), which I proposed in my IEEE journal paper published in 2018. (This paper was awarded third place in 2019 Lance Stafford Larson Outstanding Student Paper Award by IEEE Computer Society). INNOVATION 1: Via UROP, a robot/node can achieve asymptotically optimal throughput (data) from the surrounding sensor nodes by reducing the communications overhead because UROP does not need feedback to learn battery&buffer states of the nodes from which the robot collects data.

In the third tier, I apply my another novel algorithm Efficiency&Energy-Aware Data Collection Strategy (EEADCS) which I proposed in my journal paper published in 2020. (This work was awarded third place in the Poster Competition at 2021 IEEE Rising Stars Global Conference in January 2021). INNOVATION 2: EEADCS passes beyond existing approaches since we consider keeping the total energy consumption of UAV below its limited battery capacity coupled to minimum total cost data collection from CH robots by visiting an optimal portion of CH robots.

In the second tier, I apply a lightweight scalable blockchain protocol on which I am still working to improve by using artificial intelligence (AI) techniques.  INNOVATION 3: I aim to derive a more lightweight and scalable blockchain protocol.

As my solution is still in prototype, it does not serve anyone. 

On the other hand, I plan the solution to serve millions of people in one year. The mucilage in the Marmara Sea in Turkey has already affected millions of people for the last two months (Notice that Istanbul has a population of more than fifteen million people).

In five years, I aim my solution to be globally used in poor and developing countries to have resilient ecosystems.

Dr. Ömer Melih Gül

I have already published, submitted, and prepared several papers/chapter on computer&communication networks, IoT, UAV, robotics, routing, scheduling algorithms, blockchain and artificial intelligence. Besides, I have already reviewed more than 100 papers mostly for IEEE journals.  I have worked on this solution for almost eight years (since the 2013 summer when I started work on the first tier of this solution). 

One of my journal paper "Asymptotically Throughput Optimal Scheduling Policy for Energy Harvesting Wireless Sensor Networks" was awarded 3rd place in 2019 Lance Stafford Larson Outstanding Student Paper Award by the IEEE Computer Society (the algorithm in the 1st tier of this solution).

My another work "Efficiency-Aware and Energy-Aware Data Collection via UAV with Limited-Capacity Battery in Robotic Wireless Sensor Networks in Post Covid-19 Era" was awarded 3rd place in the Poster Competition at the 2021 IEEE Rising Stars Global Conference (the algorithm in the 3rd tier of this solution).

I am a member of the IEEE Identity of Things Working Group (P2958). (the algorithm in the 2nd tier of this proposed solution). Moreover, I submitted a journal paper on blockchain applications to Internet Technology Letters. In addition, I am preparing a chapter entitled "Blockchain-enabled Internet of Things (IoTs) Platforms for Vehicle Sensing and Transportation Monitoring" for contributing a book entitled "Machine Learning-Based Blockchain Technologies for IoTs and Big Data: Fundamentals, methods, and applications" which will be published by IET. Furthermore, I am preparing a new paper on lightweight blockchain protocols (the algorithm in the 2nd tier of this solution).

I am the Region 8 Coordinator in the IEEE Computer Society whose responsibility is to coordinate all CS professional/student chapters in IEEE Region 8-Europe, Middle East, and Africa (EMEA). Please notice that EMEA region includes not only half of the total lands of the world but also the most cultural diversity in the world. Especially because of this and my other IEEE roles, I am always trying to form and work with a diverse, equitable, and inclusive team.

In the future stages of my project, I plan to form such a diverse team. 

I am applying to MIT Solve which can provide us very good opportunities. especially because of the following reasons.

I can benefit from the funding and marketing opportunities.

I can benefit from access to mentorship, coaching, and strategic advice from experts, as well as the Solve and MIT networks. 

We can receive monitoring and evaluation support to build an impact measurement practice. This is very important in marketing aspects.

Our target population is people especially in rural areas of low-income or developing countries. Especially because of bad economies in these countries, companies may look for ways of not using costly filters that can industrial wastes from mixing the soil or water. Not using these filters sometimes causes severe environmental problems, which causes economic and psychological problems. 

As an example from Turkey in the last two months, the Marmara Sea suffers from mucilage which is caused by industrial wastes mixing directly into the sea for the last two to three decades. This mucilage in fact kills the sea by harming biodiversity and biological life in the Marmara Sea. The negative consequences are not only biological and economic but also psychological and cultural. While people watch the blue Marmara Sea to become more relaxed for decades, they watch its illness appearing with mucilage to go towards its death for two months. 

As a person living and loving the Marmara Sea in Turkey for three decades, I am unfortunately among such underserved people for the last two months because of this mucilage. Therefore, I can understand the needs of such underserved people, and I benefit from this unfortunate experience as I develop my solution.

To overcome such problems, we need scalable and verifiable monitoring and data collection to track ecosystem conditions, such as biodiversity, carbon stocks, or productivity. If we use such a monitoring and data collection system, then we can detect such environmental problems at their initial phase and take necessary precautions to avoid the later stages of environmental problems like mucilage.

To solve this problem of resilient ecosystems, I provide a UAV-assisted robotic monitoring IoT system for scalable and verifiable (secure, transparent and immutable by blockchain with AI) monitoring and data collection to track ecosystem conditions, such as biodiversity, carbon stocks, or productivity.

My three-tier solution with a UAV-assisted robotic monitoring IoT system is qualified for the GM Prize because it helps create smart, safe, and sustainable communities around the world by considering monitoring and data collection to track ecosystem conditions for resilient ecosystems. 

Our target population is people especially in rural areas of low-income or developing countries. Especially because of bad economies in these countries, companies may look for ways of not using costly filters that can industrial wastes from mixing the soil or water. Not using these filters sometimes causes severe environmental problems, which causes economic and psychological problems. 

As an example from Turkey in the last two months, the Marmara Sea suffers from mucilage which is caused by industrial wastes mixing directly into the sea for the last two to three decades. The negative consequences of this mucilage are not only biological and economic but also psychological and cultural. While people watch the blue Marmara Sea for getting more relaxed for decades, they have watched its illness appearing with mucilage to go towards its death for two months. 

To solve this problem of resilient ecosystems, I provide a UAV-assisted robotic monitoring IoT system for scalable and verifiable monitoring and data collection to track ecosystem conditions, such as biodiversity, carbon stocks, or productivity. With such a system, we can detect such environmental problems at their initial phase and take necessary precautions to avoid their later stages like mucilage.

My three-tier solution with a UAV-assisted robotic monitoring IoT system is qualified for the Minderoo Prize because it uses innovative technology (blockchain, AI, IoT, UAV, robots, networking protocols) in the seas/oceans to help improve fisheries monitoring, eliminate illegal fishing and forced labor, and develop a supply chain management especially in developing and poor countries. 

We propose a UAV-assisted robotic monitoring system where we use UAV (called DRONE if we consider commercial use) and a robotic&wireless sensor network that consists of clusters of robots and sensor nodes.

In the first tier of our solution, we use a time-aware and energy-aware scheduling algorithm UROP for each robot to collect data from surrounding sensors. It reduces the delay and energy consumption of the IoT network edges each of which consists of sensors and robots.

In the second tier of our solution, we use lightweight BLOCKCHAIN protocols whereby the cluster head robots collect data from other robots in a secure, transparent, and immutable way. Here, we can use AI to achieve an efficient lightweight blockchain protocol. Thus, the robotic system becomes MORE RESILIENT to malicious attacks.

In the third tier of our solution, we use a UAV (called DRONE if we consider commercial use) with a limited-capacity battery to collect data from the cluster head robots.

The proposed three-tier, technology-powered solution uses blockchain protocols for interrobot communication in its second tier (in the robot clusters). This blockchain-powered and UAV (drone)-assisted IoT solution is qualified for the GSR prize because this solution use an innovative and sustainable approach to tackling one of the most pressing issues of the local communities (environmental monitoring) in order to alleviate poverty and contribute to a sustainable world.