Robotic fish for monitoring water pollution

Abstract

The vast majority of the earth's surface is covered by water. Some parts of the ocean are so deep that even Mount Everest would be lost into them as if it never existed. Water bodies, irrespective of fresh or salty, big or small, all of them host some of the most unique ecosystems. Mankind is known to have set its sails into the oceans for time immemorial now. But it has only been possible in recent years that they have dived inside by the means of HOVs, ROVs, and AUVs. And still, most of it remains unexplored. Every living thing from a unicellular amoeba to Antarctic blue whales including every single plant needs water to survive. Otherwise, the earth would be as barren as any other planet known so far. The key to fact that life exists on the earth is water. But unfortunately, the amount of garbage of all kinds being dumped into the sources of water pollutes them and in a long run adversely affects and endangers the living things on planet earth. As our very existence depends on water, it's indispensable to monitor and take essential steps to preserve the water quality accordingly. Not only does water avail a sustainable condition for the terrestrial inhabitants, but also is a habitat to a huge number of species within. One of the most well-known species among these aquatic animals is fish. In this work, a brief study of types of fishes along with their structural definition is carried out to determine how they propel and swim in the water with their fin and then eventually use the discoveries to biomimetically design and implement a robotic fish capable of exploring water and taking certain readings with inbuilt sensors. The thus obtained readings can be used to monitor water. The robotic fish here tries moving in the water replicating the motion behaviors of a fish. This study consists of 5 different parts. Chapter 1 provides a brief introduction of the whole idea and the classification of fish according to their swimming behavior. Fishes swim in the water using their fins. They use their fins to produce a propulsive force that pushes them forward. Depending upon which part of the fish and how it pulsates fishes can be categorized into different classes. These classifications help study fishes better. A detailed categorization on the basis of various grounds is further discussed in this chapter. A common approach to classify fishes is based on the modes of propulsion that a fish applies while swimming i.e. whether undulatory or oscillatory methods of generating propulsive forces. These two categories of fish swimming modes are BCF (body and/or caudal fin) locomotion, and MPF (median and/or paired fin) locomotion. A thing common in these modes of propulsion is that the caudal fins play the most important role in producing the propulsive force generation. In this study, a "Carangiform & Fusiform" model has been adapted for replication. The first chapter also gives a brief description of "Biomimetics" along with some of its popular applications in various fields. Later in this chapter, the overall implementation of this work has been mentioned. Chapter 2 discusses works of a similar kind. It also comprises the methods used in other similar works. The caudal fin drive mechanism can be of single, multiple, or compliant type. It is already known that the caudal fin plays the most important role in swimming and maneuvering. And the stiffness of the joint that connects the caudal fin to the body of the fish is equally important for efficient swimming. Unlike other similar works, Turfi uses a single joint method with a soft caudal fin. The outer cover of Turfi was designed using SolidWorks. The 3D model was later printed using a 3D printer. The outer body of Turfi was divided into 2 halves while designing. The first half enclosed all the electronics (including the SD card module, battery, sensors, processor, and driver circuits) and the motors. The pectoral fins are controlled using micro servo motors that help Turfi in maneuvering and the caudal fin is driven using a dc motor attached to a reduction mechanism. The other half of Turfi is the caudal tail and its mechanism that creates the oscillatory motion in the caudal fin by the means of the dc motor. The caudal fin drive mechanism converts the rotary motion of the dc motor to oscillatory motion. The front enclosure part was 3D printed using Polylactic Acid (PLA) because of its stiffness. The posterior i.e., the caudal fin was made using Thermoplastic Polyurethane (TPU). TPU is best known for flexibility. Making the caudal fin with TPU gives the caudal fin a soft and flexible structure thus making the propulsion wavy and smooth. The ESP32 used as the processor is also embedded with a WiFi module. ESP32 is programmed to create an Async WiFi server. The asynchronous server allows Turfi to take the readings and store them on an SD card even when offline. And when connected can deliver all the data collected at once. This helps Turfi to navigate and collect data irrespective of its connection to the base station. Turfi while navigating underwater takes the sensor readings and stores them into an SD card. After the completion of navigation, Turfi resurfaces and connects with the base station using WiFi and sends all the readings made during the navigation. Turfi later. These readings can be accessed using an IP provided by ESP32. These details are discussed in Chapter 3. As this study progressed further it was seen that Turfi can be programmed in various ways to accomplish different tasks. In the 4th Chapter, the results of two different tests are included. In the first test, Turfi was programmed to take readings at a certain depth (i.e., 20cm). A PID controller using PID Library by Brett Beauregard was used to track the depth based on the readings from the depth sensor. The second test was similar to the first one except that Turfi was instructed to take left and right turns. 5th Chapter concludes this work by describing the complexity of multi-fin locomotion underwater. It also briefly explains how Turfi can be developed in order to accomplish further. Upgrades such as a camera to record underwater, sensors to measure pH, oxygen level, salinity, etc. can be attached to Turfi. These sensors can help Turfi monitor underwater in a more detailed way. An exit mechanism is also proposed in this section. The exit mechanism would help Turfi resurface in case the battery is below a certain level or once the navigation is complete. Once atop, the whereabouts of Turfi can be known using GPS. There have been works of similar nature done priorly. But most of them tend to focus on a descriptive analysis of the swimming behavior of a fish and then replicating it. In this work, the scope has been slightly widened by adding the sensors to make required readings. One major hindrance similar to the ones of previous works i.e., limitation to wirelessly communicate well is experienced while working on this project as well. Thus, a different approach is applied in this study. In this approach, Turfi is instructed to follow a certain navigation route. While navigating underwater, Turfi also stores the sensor readings on an SD card. These data can be retrieved wirelessly from Turfi over WiFi. Thus, obtained data can be used for further processing.