Over-Watering and Under-Watering are the two concern-able scenarios actively addressing the water conservation which is one of the major global challenges. There are trained gardeners who can water the plants regularly and maintain the gardens and other landscape plants effectively. But how much we control the water wastage from human hands while watering plants, there is a considerable error happening always, and we can control it by autonomous systems. Project "Green-Globe" is our idea to create some momentum in addressing this issue. We're focusing to develop an authentic system with using which we can utilize the natural resources ( i.e., Water) properly to grow the plants effective and efficiently. So, the idea is to develop an autonomous irrigation system to water plants with which we can automatically water the plants by understands and calculating the primary parameters like plant genetic information, moisture in the soil, humidity in atmosphere and secondary parameters like temperature and electrical conductivity of soils. The realistic approach of our project comes in a long run, but it will create a benchmark for the initiation of connecting the edge technology of INDUSTRY 4.0 with global challenges of today. Project Green-Globe delivers the essential requirement i.e., growing the plants effectively and efficiently by regulating the Over-Watering and Under-Watering. The outcome also addresses to saving the water and conscious usage of the water while watering plants at houses and other areas.
The developed system is able to regulate the water wastage, and is able develop ML and AI models from understanding the plant's genetic information and the rate of it's growth, and also using climatic conditions which were collected via Internet APIs and cloud. The developed models helps to perform better autonomous irrigation methods, and could also be helpful at concepts of terraforming other planets.
Water is a vital factor in human life and for the existence of other habitats. Easy access to safe water for drinking, domestic use, food and production is a civic health requirement. Therefore, maintaining a water quality balance is very essential for us. Otherwise, it causes serious health problems to humans. Water contamination has been studied as one of the leading causes of death and illness in the world. Many people die from contaminated water every year. One reason is that public and government ignorance and the absence of water quality checking systems cause severe medical issues.Water contamination is also a serious issue in industries, irrigation and aquaculture.
Traditionally, water quality detection is done manually when water samples are taken and sent to the laboratory, but this process requires a lot of time, cost, and human resources. These techniques do not provide real-time data. By considering these challenges, we have come up with an idea to design a Water quality analyzer to check the quality of the water used for different purposes.
The Process starts from taking the real time data from the water bodies using sensors and type of water need to be checked must be selected from the mobile app. FPGA Board processes the collected data and compares it with the standard data in order to assess the water quality.The quality parameters of the water and the quality of the water will be sent to the mobile app using IoT Technology. If the quality of the water is below the desired levels, an alert will be sent to the user. In this way we can have continuous real time water monitoring.
With climate change and water scarcity, arid countries' policies aim to conserve dams’ water for domestic and industrial use only. Due to a lack of budget, having no other alternative, Small-farms crop production turns to the use of innovative low-cost solutions for irrigation and livestock. The proposed project outlines a new approach supporting agricultural agencies and policies at all levels, livestock professionals, smallholding farmers, and local populations, to stabilize the ecologically unsustainable exploitation of the water on dry-lands. The proposed approaches aim to implement Edge Artificial Intelligence on Intel FPGA and Microsoft Azure cloud computing for the prediction of water quality and its evolution, manage an innovative irrigation process, livestock watering points, as well as artisan activities (pottery...).
The high level of river pollution in industrial and metropolitan environments negatively impacts the ecosystem and raises the government's cost of maintenance and cleaning of those areas. A significant number of rivers, though, are never or rarely cleaned since there is not enough data about their pollution level, nor where the garbage foci are. Hence, a significant portion of all the river waste worldwide is never discovered. It remains unattended, increasing environmental degradation and furthering the impunity of bad actors that pollute rivers without having their actions put to judgment.
We propose a river waste monitoring system composed of an UAV equipped with an image capturing and processing device based on a FPGA. The proposed system also includes support stations with solar panels that will send the collected data to a cloud application while also sending data back to the UAV about its energy status.
The UAV will be capable of flying over the river waters and the riverbank in search of waste. It will also have a small compartment onboard, that will be used to collect water samples, which will then be sent back to a support station for testing.
The support stations will aid the UAVs by collecting solar energy to charge them and analyzing the water collected by the UAVs.
The cloud application will have a dashboard that will display the garbage accumulation spots on a map alongside pictures of the trash and historical data.
The FPGA is an essential part of the system because it will provide the computing power and precision needed for the obstacle and waste recognition algorithm to work in real-time while also being energy-efficient.
The project's expected outcome is to have a relatively low-cost, self-sustainable autonomous system that can be easily deployed on various rivers and efficiently map the river and riverbank area for garbage accumulation spots while also assessing the water quality. This system will provide the local government and agencies with real-time and detailed data about the river's health and waste accumulation spots. Furthermore, the data gathered will be valuable in policies and efforts to restore the river's condition and educate the local community about correct waste disposal practices and other ways of ensuring the nearby river's well-being.
Prototype of an Intel FPGA-based automatic irrigation system for soft fruit farms in Perthshire, Angus and Fife, Scotland, UK
Our venture is coming up with the cutting edge End-to-End product which can help the marine species and over a 5-10 years course wild capture would be rejuvenated naturally with the ultimate solution what we offer with the existing Hardware/Software but integrating and applying it for a unique way.
Blind Fishing and overfishing has made the marine resources / wild capture as no longer a bottom less fishing.
This overfishing put a trouble to 1/3 of world population especially the under-developed and developing countries who rely ocean as their cheap protein.
The project vision is to create a modulo IoT network that could be easily modified and applied onto various types of farms and greenhouses to help optimize water use, give insights, and impact the health of crops and the surrounding environment. Hence, increase the quality of the product going to the market and reduce the wastes that will contribute to long-term sustainability.
An IoT network will include a master node made of the FPGA Cloud Connectivity Kit, which will be responsible for collecting data from the sensor nodes, communicating with the cloud along with controlling the actuators that will affect a specific crop on the field.
Each Sensor Node will have its own MCU connected with a Soil Moisture and pH Measurement sensor (CN0398), a Volatile Organic Compound (VOC) Detector (CN0395), the Light Recognition System (CN0397), and potentially any other sensors that the customer requests. The data collected from these sensors will be transmitted to the Master node through wired RS485, wireless LoRa, LoRaWAN or other local transmitting methods (depends on specific setup). The moisture data collected will be used to control a watering pump through an isolated Contactor. pH or other soil qualities data can be statistically displayed to give the user insight into what should be adjusted to the fertilizer. Moreover, the VOC and Light data can be used to conditioning airflow in the greenhouse and changing lighting components to provide the best environment for the crops to thrive.
The cloud-based service will be in contact with the master node to connect the user from anywhere around the world to monitoring and controlling their farm. Besides, the cloud is also responsible for updating the system's firmware Over-The-Air (OTA) and store the processed data from the FPGA for further analysis and future improvement.
If time permits, edge computing Machine Learning will also be applied to the master node to automatically control the watering, lighting and air ventilating based on the crop that is being monitored, hence reduce the network bandwidth, contribute to the long-term energy efficiency compared to applications that do most calculating on the cloud. This network can be scaled up with many Master Nodes, each responsible for specific crops in a greenhouse or a farm, connected all together and monitored by the cloud or by a local Grant Master Node. We are expected to test the system on a greenhouse facility in Vietnam after finishing the prototype, which will give us a better insight into how the system operates.
Through the project, besides expecting to learn a heap of new useful knowledge, our team hopes to create a foundation for improving the efficiency of watering and energy usage in agriculture, especially in developing countries such as our hometown Vietnam.
The project is aimed to improve water distributor's capacity so everyone can use water even during dry and drought season.
Since only 3% of the world's water is usable by humans and other living things, it is necessary to be more sensitive in this regard. According to the article published by Worldbank in 2017, it was mentioned that approximately 40% of the world's population lives in water-restricted areas, and it is estimated that approximately 1.8 billion people will live in areas without water by 2025 . Therefore, we should use water resources more efficiently. Abundant use of water in agriculture will create major drought problems in the future. According to the Worldbank, a 60% increase in agriculture is required to feed 9 billion people by 2050, which will increase water use by 15% . According to the CUESA (Center for Urban Education about Sustainable Agriculture), it is mentioned that in order to prevent excessive water use in agriculture, farmers should monitor the weather conditions regularly, while at the same time, the moisture level on the soil and plant should be measured continuously. It is stated that a system to be created by monitoring these values will save water usage .
In our project, we are planning to develop a system that will reduce water use in an agricultural area. While this system will constantly measure the moisture content in the soil, it will also have a structure that will stop the irrigation system from working in case of rain. We will use the CN-0398 coded soil moisture measurement system to measure the humidity level. In addition, we will check whether it is raining with the HL-83 rain sensor. We plan to reduce unnecessary water use by combining these two systems. After analyzing whether the soil needs water or not, we plan to control the irrigation level by sending the necessary data to the cloud system with the ESP8266 Wi-Fi module in order to analyze the last year’s data. We aim to make a measurement every 10 seconds by the system and to send information about the analysis made according to these measurements to the cloud system in less than 5 seconds. Analyzes will be made with the DE10-Nano Kit.
Expected sustainability results and projected resource savings:
The threat of extinction of the world's waters is a very important problem for sustainability. We think that this project will make significant contributions to sustainability. According to a report published in Nature World News, 30% to 50% water savings were made with the smart irrigation system . We plan to save at least 20% of water in irrigation in agriculture. We believe that thousands of tons of water can be saved if the system is started to be used actively in agricultural areas.
 “Water resources management,” World Bank. [Online]. Available: https://www.worldbank.org/en/topic/waterresourcesmanagement. [Accessed: 19-Sep-2021].
 “10 ways farmers are saving water,” CUESA, 30-Jun-2021. [Online]. Available: https://cuesa.org/article/10-ways-farmers-are-saving-water. [Accessed: 22-Sep-2021].
 M. Brown, “Smart irrigation System 'listens' to Plants cries to reduce water use up to 50%,” Nature World News, 03-Sep-2021. [Online]. Available: https://www.natureworldnews.com/articles/47332/20210903/responsive-drip-irrigation-irrigation-system.htm. [Accessed: 23-Sep-2021].
River water surface floating object monitoring system uses sonar probe to transmit and receive sound waves as the front end of the system detection. When working, the master control device controls the sonar probe to transmit a certain frequency wave, when there is a floating object in a specific area, the wave transmitting forward meets the obstacle and will be reflected to the sonar probe, the master control device can calculate the distance s from the sonar probe to the floating object according to the time difference t from transmitting to receiving and the propagation speed v of the wave in the water, and the properties of the floating object can be judged by analyzing the difference between the return wave and the transmitting wave. At the same time, the main control device receives the information returned by the sonar probe, controls the camera device to shoot down the image of the specific area, and transmits all the above information to the cloud through the wireless transmission device. The function of monitoring floating objects on the water surface of the river is completed.
Singapore is a highly industrialized country which is one of the top countries with high population density. Trees and vegetation can be found in every block but is limited in every multi-storey residential building like HDBs and Condominiums. The projects aims to promote local hdb/condo residents to implement and improve their existing aquariums into a sustainable aquaponics which helps to reduce the carbon footprint and reduce the water usage.
The main focus is on a smart irrigation system which is a vital need in today’s world. The twenty-first century deals with technology and automation, making our lives easier, adaptable, and cost-effective. In our country, India is divided into two groups of people, the agro-based farmers whose livelihood depends on food production and on the other side the consumers who depend solely on the consumption of food produced by the farmers. Both have an interdependent link. India an agriculture-based country, it is very important that the methods used for agriculture are efficient to satisfy the increasing demand. This led to the origination of smart irrigation system which is one of the smartest methods used in agriculture. It provides an automatic irrigation of crop fields and does not require human involvement. It keeps the track of the water level as well as soil moisture content. This ensures the proper and healthy growth of plants. The major factor involving agriculture is the depletion of water which keeps on increasing day by day. The smart irrigation system also resolves this issue as the water is conserved by the automated water system consisting of a sensor that senses the climatic data such as humidity, soil moisture, and water level. The agriculture field is irrigated based on this data and water flow.