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.
Our project will be based around wastewater detection in rivers and lakes. Specifically we will be testing in the Pittsburgh rivers region because in times of heavy rainfall, waste tends to end up in the rivers due to infrastructure problems. Our device will be able to tell the concentration of wastewater in the location where the sensor is placed.
Nairobi city ; as was formally known as a place of cool waters gets its freshwater from 3 main rivers and dam ; Ngong river ,Nairobi river and Ndakaini dam.
These rivers pass through the industrialized and informal(slum areas) where polution is very rampard . One notorius area is the dandora dumbsite in the poorest slum area in the east .
The rivers are full of industrial chemicals , human wastes,used oil plastics etc .
Maji Safi Mazingira safi is a collaborative project between the Focuslense (intelligent imaging and mapping company) ,the local government environment agancy NEMA; National Environment Management Agency and local community to help reduce pollution ,identify the water pollutants ,chemicals ,plastics etc . The solution involves installation of water ph , chemical level and image (video ) monitoring systems along the river, especially where pollution is rampant.
an FPGA kit is used with remote sensors and cloud connectivity to record chemical and pollution levels in the water and transmit to Azure cloud IoT . Azure AI image and video analytics is also used to analyze sources of pollution.
Focuslense electronics is an engineering company established in 2016 to help tackle challanges affecting poor and marginalized communities around Nairobi ,using computer vision ,AI ,IoT and 3D printing technology .It consists of a team of 5 software,hardware engineers,data scientists and a consultaing city planner.
Swimming Pools provide the perfect evaluation testbed for monitoring and control of water chemistry. PH and Chlorine levels must be monitored and controlled for the health and safety of the swimmers. Given the destabilizing effects of solar exposure, air temperature, and rainfall, additional chemistry supports stabilizing the Chlorine and PH levels. Additionally, pumps circulate the pool water through filters which impact energy consumption. Using a 28 thousand gallon pool, we intend to demonstrate the use of FPGA’s for data collection and Cloud computing for control and monitoring of water chemistry processes. Stretch goals will include using weather forecasts to anticipate and hopefully minimize both chemical and energy usage.
Because other water applications have similar issues, this work will apply to other consumers; people, livestock, and agriculture are prime examples.
We propose to develop a miniature and low power Soil Moisture Radar (SMR) designed to be mounted on either a land based farm tractor or a low flying airborne platform such as a drone. A GPS module will allow the system to construct soil moisture maps during normal daily farm operation. These maps will allow managers to view the field as a whole and to identify irrigation patterns that are not as easily recognized at ground level, reducing water use and allowing selective crop irrigation thereby reducing water consumption and increasing crop yield.