The main idea of the work is control water level through channels of the drainage system and therefore reducing water level in the extra filled channels. To get the expected result, the system should develop by: (i) electronic sensor, computational nodes and “smart” gates. The main sensors are
a. Ultrasonic Sensor: Ultrasonic sensors are utilized for distance estimation of water with an exactness up to 3.0 mm. The unit is fit for estimating distance with a range of 2.0–400 cm with an accuracy ± 3.0 mm. The detector circuit is kept so that it isn't in direct contact with water to accomplish sturdiness of the detector circuit. For estimation reason, the detector HC-SR04 requires10-µs beats as trigger information. It transmits 8 cycle pulse of ultrasound of frequency 40 kHz and creates its reverberation. The distance is obtained by estimating time taken by ultrasonic signal return back after colliding with the article [19]. The ultrasonic sensor acts as an information source to the Arduino microcontroller. The information is processed by the microcontroller, sent to the dependable authority through Wi-Fi which require just couple of moments. Nonetheless, the receiving signal too relies upon web speed accessible right then and there of time.
In this paper, we have studied the various waste material which are the main reason for clogging of drain. These are to be squander materials for example, food, plastic trash containers, and house hold squander materials. In most of the city, it is found that the vast majority of the waste product contains biodegradable food waste like cooked and uncooked vegetables, food grains, eggshells, fish/meat bones, bloom and natural product squander including juice strips. Moreover, non-biodegradable squanders such as plastic sacks, jugs and can, slow down the current present in the drainage system. Presence of waste creates blockage, which in term increases level of water; further it will be one of the main cause of flood which can be prevented by our system because it can sense level and takes necessary steps or provides alternative way to avoid any further increasing of water level in drainage system.
This is a distributed system of sensors and actuators which is established on an urban drainage arrangement. Mainly we design the structure with a number of moveable gates, acts as actuators, and sensors which monitor water level and, hence, the degree of filling in each conduit.
The ultrasonic sensor measures the level of water inside the drainage system. The information is processed and decision is taken for dynamic regulation of gates. The main idea is when any channel (drain) is overloaded, its water is diverted to a less overloaded channels to prevent overflowing from drainage system and which in turn prevents flood also. Solenoid valve, flow sensor and HCSR04 are the main sensor used in this work.Here, the entire drainage system is assumed as number of computing nodes which are connected to sensors and gate actuators i.e., solenoid valve. Every computing node can link only with its neighbourhood, i.e., sensors, actuators at other nodes, it can reach through wireless connection. The genetic optimization algorithm is used for this work. The main function is to distribute equally the degree of filling of the conduits thus preventing overflow phenomena as far as possible.
Primary trials were done using \({MATLAB}^{R}\) software which simulates the operation of a typical urban drainage network controlled by moveable gates during heavy rainy events [20]. The actual time regulation was added by means of customizing \({MATLAB}^{R}\) software permitting it to real-time communicate with a separate multi-agent Java controller implemented using rainbow architecture. The experimental results have proved that our experiment gives a positive effect on the total hydraulic performance of the network as it is intelligent to avoid flooding events that would occur in the original network.
After finding suitable results in simulator, the system is implemented as described below:
a. Arduino platform is used for processing data of solenoid valve and HC SR04. The HC-SR04 detector work as an input device to the microcontroller. The data are managed by the microcontroller and transmitted to the responsible authority through Wi-Fi which take only few seconds. Yet, the reception depends on internet speed available at that instant of time. These devices arranged inside the drainage network. It consumes very low amount of battery and size are small also.
Solenoid valve operated smart gates, automatically regulates the gate movement, made up of mobile plates rotating around a horizontal hinge. On the other hand, the gate is entirely open when the plate is parallel to the flow. The computational nodes collect information from detector and on the whole intricate the acquired data to trigger appropriate actuations on the gates. The combined calculation of the network of nodes supplies the entryways with a "smart" behaviour.
Smart gates are placed at the place of the network where sub-networks are associated to a main channel. Figure 8(a) shows the actual point for implanting the gates, while Fig. 8(b) represents the gates insertion in a case of a realistic web. Each computational hub has a partial perspective of the network as it reads only from sensors located in its spatial neighbourhood. In the same way, it can activate only on its neighbour gates.
b. To measure the rate of flow of sewage, flow sensor is used. When water passes through the flow sensor’s rotor, rotor rotates. Its speed changes with a different rate of flow. The hall-effect sensor outputs the corresponding pulse signal. This one is appropriate to detect flow in water drainage system. The sensor circuit is mounted in such a way that it is not in direct contact with the sewage water to achieve durability of the sensor circuit. The flow rate of drainage water is calculated by,
\(flow rate in L/hr=flow frequency \times 60 min/7.5Q\) (iv)
Where, Q = V × A, and Q is flow rate/total flow of water through the conduit, V is average velocity of flow & A is cross sectional area of conduit.
Microcontroller: The optimal low power advanced microcontroller is a one of the challenges of this work. The data collected by sensors is processed by the microcontroller and after processing it is sent to a remote server via a wireless link. Uninterrupted internet connection is required which the main limitation of the work. The state of drainage is transmitted to the end-user and can be viewed in smart gadgets like cell phone, tablets or other navigation systems with internet connectivity. Figure 9 shows a schematic diagram of the proposed system and flow of operation. The required information obtained by the sensing units is available after processing to the end user.
Table 1 Comparison of Wi-Fi network with other network technologies
Category
|
Zigbee
|
Bluetooth
|
Wi-Fi
|
Tele Communication
|
Single point coverage range
|
50–300 (m)
|
10 (m)
|
50 (m)
|
Several (km)
|
Network expansion capabilities
|
Automatic
|
None
|
None
|
Relying on existing network coverage
|
Complexity
|
High
|
Medium
|
High
|
Medium
|
Time for network connection
|
30 s
|
10 s
|
3s
|
Several seconds
|
Fee
|
None
|
None
|
None
|
High
|
power consumption
|
Low
|
High
|
High
|
Medium
|
Data rate
|
250 Kbps
|
1 Mbps
|
1 to 11 Mbps
|
Norma1ly 19.2 Kbps
|
As the power consumption is an important factor in remote area, Arduino Pro Mini (Atmel 328p) (consumes 6.48 mA current during wake condition and 4.3\(\text{μA}\) during sleep condition) is used instead of common Arduino Uno (consumes 45 mA current during wake condition and 6.2 mA during sleep condition. It runs at 16MHz clock. It comes with on 40 pin Integrated chip. The functional Voltage is 3.3V. The microcontroller is enabled for accepting up information from sensors and transmits it to the internet through a network interface. The below Table 2 represents the comparison of various microcontroller board based on the ATmega328P chip which are Pro Mini and Arduino Uno.
Table 2
Comparison of various microcontrollers and their current consumption during sleep and weak condition
VCC
|
Clock Speed (MHz)
|
Wake Current (mA)
|
Sleep Current (µA)
|
5.0
|
16
|
15
|
6.2
|
5.0
|
8
|
9.03
|
6.2
|
3.3
|
16
|
6.48
|
4.3
|
3.3
|
8
|
3.87
|
4.3
|
Battery: Battery plays an important role for for a wireless device placed in distant place. Hence, to enhance lifetime of battery, the code is written in such a way that instead of remains ‘ON’ continuously, the controller remains in ‘sleep mode’ most of the time and only remains on when we want to take an action or read a sensor value. This reduces the current to somewhere close to 4.3uA. A standard Arduino (Uno for instance) consumes more than 15mA. For a typical Alkaline 9V block with capacity of approximate 450mAh, will drain out in 30 hours (450mAh/15mA). On the hardware side also, we made some adjustment because things like standard USB interface, power regulation and some LEDs that make Arduino hardware great are also increases current consumption. We are using Arduino Pro Mini and makes it active only five times per day for only ten second and keep in sleep mode for rest of times in a day. In the model there are two sensors which are ultrasonic sensor & flow sensor. The cuKrrent consumption for ultrasonic sensor and flow sensor are 10mA and 15 mA respectively. The software programming is such that devices are becomes on only five times per day. All other time they remain in off and controller remains in sleep mode.
Therefore, total consumption of average current
\(\text{Average current during active/weak condition}\) \(=\frac{\left(\text{15mA+1irment is minimum0mA+6.48mA}\right)\text{×10s}}{\text{10s}}\times 5\left(\text{times/day}\right)\) \(\text{=157.44mA}\) (v)
During sleep condition current requirement is minimum, therefore it is not taken under consideration.
Calculated battery life time
\(\text{=450mAh/157.44mA}\) \(\text{=2.86 hrs}\)
Therefore, we can use it for 2.86 hrs.
\(\text{Total}\text{} \text{duration the model is used only 50sec}\) \(\text{No.}\text{}\text{ofdays it can use}\) \(=\left(\text{2.86×3600s}\right)\text{/50s}\text{}\text{}\text{times}\) \(\text{=205 days }\)
After receiving the information from various sensors of system, it has been transferred to the microprocessor for processing, which further uploaded to the cloud server. In order to do that we using 2400–2484 MHz band based (the IEEE 802.11 b/g/n) Wi-Fi transreceiver module. Level of water in the drain is accessible on the website of cloud server. Alarm messages were sent to the respective authority, for identified overflow of the drain with location for obtaining suitable measures.
Access Network Interface: The information obtained must be sent to a remote server via a wireless link. In our proposed system, we utilize Wi-Fi as a network access technology. We used Wi-Fi serial module ESP 8266. The Wi-Fi unit provides an exact interfacing with the microcontroller used. This module comprises of a 32-bit microcontroller, ADC, UART, PLL and memories.
It has its own self-calibrated RF which allows it to operate under all working situation and requires no external RF parts. Access Network helps to send details of drainage system at the receiver side. Figure 10. represents circuit arrangement of proposed system.
In our work, the cloud server is additionally interfaced with mobile application. The application allows us to visualize our data channels in a simple way by only providing the channel ID and we are ready to check the status of drain i.e., fill up condition. By observing status responsible authority can take suitable action, not only that if the level is above certain fixed level, nearby alternative gate will open which allows drain water to pass through another conduit.
End user Visualization: This IoT based system will detect the blockage in the sewer lines and offers the early alarms so that responsible authority can clean it as early as possible.