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ENGINEERING MINOR THESIS-1

1) AIM:

The aim of this project involves designing and implementing a distributed real time data acquisition system, to be integrated through a SCADA system by using an open platform communications (OPC) protocol

2) OBJECTIVE:

The objective of this project includes:

Developing a Raspberry Pi controlled SCADA based sound pollution monitoring system

Collecting and monitoring the real-time noise level of university environment via the OPC server

3) ABSTRACT:

In recent times, noise pollution being a frightful problem. It is essential to control and properly monitor the situation so that the required actions to control the situation can be undertaken. In this project, the Noise Intensity of a university campus is monitoring by an IOT-based method.

The suggested technology consists of the Sound Intensity Detection Module, which is connected to Raspberry Pi and integrated through a SCADA system and it uses the data communication protocol (OPC). The sound intensity is detected using the corresponding sensor.

Here, Raspberry Pi act as an RTU which stores the real-time value of field sensor in its memory and this memory is assigned as
OPC Tag, so that the OPC server can constantly monitor the real-time value.

4) INTRODUCTION:

Noise pollution is a rapidly growing problem these days. It is essential to monitor the noise pollution levels to ensure a healthy environment. The smart monitoring systems are needed due to the rapid increase in infrastructure and industrial plants, environmental issues.

Internet of Things (IoT) known for its high efficiency, low cost and versatility allow interaction between device and humans. It becomes a communication medium from human to the device. The earlier data collecting was a lengthy process because collector had to travel a long
distance to fetch data after which the analysis was done.

This was a time-consuming process. Nowadays, sensors, microcontrollers or programmable logic circuit connected to the internet which makes the system more flexible, accurate and less time consuming for monitoring the environmental parameter. This makes a smart environment, when the environment merges with sensors and devices to self -protect and self -monitor. The environment interacts with the objects with the help of embedded intelligence.

In this project we are using a noise sensor and Raspberry Pi microcontroller, it forms a programmable logic circuit which is integrated through a SCADA system, to monitor the fluctuating environmental parameters.

5) PROPOSED SYSTEM:

Noise pollution has a dangerous impact on human life. The sound coming from honking cars, industries, factories, and heavy machinery are the general causes of noise pollution. Government prescribed certain noise standards that need to be maintained

Code	Area	Day Time	Night Time
A	Industrial Area	75	70
B	Commercial Area	65	55
C	Residential Area	55	45
D	Silence Zone	50	40

The proposed distributed data acquisition system is for monitoring noise levels around the university campus to make the environment intelligent with the objects through the internet of things  via wireless communication. The proposed model is shown in figure1 monitor the environmental parameters, which is more adaptable and distributive in nature.

The proposed architecture is explained in a 4 hierarchy model with the functions of each module developed for noise monitoring. The proposed model consists of 4-hierarchy. The hierarchy 1 is the university environment, sensor device and Raspberry Pi in hierarchy 2, hierarchy 3 is the sensor data acquisition and decision making with sending data to OPC server and SCADA HMI in hierarchy 4.The proposed block diagram is shown in figure 1.

Figure 1: Block diagram of proposed distributed data acquisition system

The proposed architecture consists of the following modules, namely, the, the Sound Intensity Detection Module LM393, the Raspberry Pi module, the Wi-Fi router and finally the SCADA HMI

LM393 Sound Sensor

In this project, LM393 is used to monitor the sound pollution. It comprises two independent voltage comparators which are operate from a single power supply over a wide range of voltages. The difference between the two supplies is 2V to 36V, and VCC is minimum 1.5V more positive than the input CM (common-mode) voltage, then dual supply operation is possible. The output signal voltage is sent to Raspberry Pi, when the sound sensor detect sound and which again performs the suitable steps required for monitoring the parameter. The Specifications of the sound sensor:

Figure 2: LM393 sound sensor

• Operating voltage 3.3V-5V
• Output model: digital switch outputs (0 and 1)

Raspberry Pi Model 3B

Raspberry Pi 3B module is an ARM-based credit card sized Single Board Computer created by Raspberry Pi Foundation. It has Wi-Fi and Bluetooth module present in it. By using this module, we can send the collected digital counterparts of the parameters, to a Cloud-based storage area via the internet. The saved data is also used for analysing the information collected, on a periodical basis.

SCADA Human Machine Interface (HMI)

Supervisory control and Data Acquisition (SCADA) system has a human-machine interface which is a core component of a remote monitoring and controlling system. The data collected from Remote Telemetry Units (RTUs) and Intelligent Electronic device (IEDs) displays at the interface and also allows an operator to control the RTUs / IEDs or connected equipment. It is also referred to as a SCADA Master, which provides useful extensions for network alarm management.

6) WORKING METHODOLOGY

The main objective of distributed data acquisition Sound Monitoring System is to monitor the noise level in the university campus to control the problem of sound pollution. LM393 Sound Detection Sensor detects sound above a standard threshold value around university environment.

Here, the LM393 acts as the field device and Raspberry Pi function as an RTU in the proposed SCADA system. It checks for sound levels and sends a High signal to RTU and which again performs the required steps for monitoring the parameters. We are using Python language to interact with GPIO pins once the Raspberry Pi is up and running. The GPIO pins act as an interface to the LM393 sound sensor. Adafruit GPIO python library and the Adafruit LM393 library have to pre-load on the Raspberry Pi. The Raspberry Pi and sound sensor set up in hierarchy 2. The sensing side of the architecture is shown in figure 3.

Figure 3: Flow diagram of sensing side of the architecture

This proposed architecture involves cloud-based monitoring of the sound intensity with the help of internet. The sound intensity after being detected using the corresponding sensor is processed by cloud-based monitoring module with the help of the Wi-Fi module in Raspberry Pi which analyses the information on a periodic basis. RTU stores the real-time value of field sensor in its memory and this memory is assigned as an OPC Tag, so that the OPC server constantly monitors the value.

The tier-4 fitted with SCADA HMI ensures that the university authorities are informed about any unfavourable condition. The hardware side of the architecture is as follow:

Figure 4: Block diagram of hardware side of the architecture

7) Literature Review

A) HISTORY

Pollution parameters can be monitored by carrying out some research works which make the environment smart in that area. The following section briefs about techniques and methods which were used in the past.

The environmental parameter can be monitored by Zigbee wireless sensor network, proposed by L.Ezhilarasi et al.(2017). In this scheme, data is stored and retrieved by RFID to an RF integrated circuit through an electromagnetic transmission. The data collection at any time and place is done by WSN gateway method. . However they had a few drawbacks such as low transmission rate and are  not secure to be used for official private data. This architecture does not suit outdoor communication.

In order to rectify these drawbacks and to support the outdoor wireless communication, a promising wireless communication using GPRS module was developed. As part of research undertaken by Mahantesh B Dalawai et al.(2017). Pollution level can be monitored by the GPRS/GSM module and a web server. In this research, pollution level can be monitored by the internet as the smoke and noise sensor will be uploading data to a server computer at every instant of time.

Another research study proposed the concept of the smart city is based on wireless technology and communication. Arduino module interacts with air and sound sensor which processes the data and transmits it to the application. Data is monitored by air and sound sensor which is later uploaded as digital data on the cloud, which analyse the data and will be notified accordingly.
This cost-effective monitoring system in which information will be collected by the sensor and upload to the cloud, where it can be accessed at any time. (Fioccola et al., 2016)
 
This proposal has given the idea of the real-time parameter monitoring system. Smart environment monitoring deploys wireless sensor network all over the city, moving public transport system buses and cars. By accessing this network, the behaviour is collected as a streaming database which detects environmental conditions and monitoring data from stationary nodes and deployed to public transportation buses and cars.

The concept of the internet of things implements an idea of energy saving by the management of computer and air-conditioners. WSN and IoT based smart homes and their extension to smart buildings aims to design and develop reliable, efficient, economic and realistic wireless sensor network. Theses use actuator and sensor nodes which deployed to the home environment. They generate real-time data related to data usage.( Wang Lin Tuing , 2013)

B) Internet of Things (IoT)

IOT embraces each physical object into a network which has changed the concept and realization of IoT. The architecture of IoT has 3 segments which are the hardware segment, middleware segment and the presentation segment. The hardware or embedded communication hardware refers to the connection of sensors. The middle wave is responsible for data storage, computation and data analysis. It is also called cloud environment.

The presentation segment interprets data in an easy and understandable format. IOT must possess the capabilities of communication, cooperation, addressability, identification, sensing, actuation, embedded information processing, localization and user interfaces (Himadri et al., 2016).At the hardware segment, sensor devices in wireless sensor network act as communication node and is expected to be a key technology for different IoT applications such as home automation. These collect and send data to the data centre. For wireless sensor network, communication and measurement are the two important functions (Khan et al 2012)

As part of the research was undertaken by Saha et al.(2018) discussed the IOT –based method to monitor the environmental parameter was introduced. Based on assertions, it consists of 4 modules which are the sound intensity detection, the Air-quality index monitoring, cloud-based monitoring module and the anomaly warning module. The sound intensity and air quality were monitored using the respective sensor. The data acquiring with the help of Wi-Fi module present in Raspberry Pi was done by cloud-based monitoring module and which was transmitted to the anomaly notification module to alert the users.
 
In this project, I am planning to implement a distributed data acquisition system which collects and analyses real-time data which is connected to the SCADA system by using an OPC protocol. The proposed model helps to monitor the real-time value via the OPC server in which the RTU memory assigned as an OPC tag.

9) PROGRESS:
• Initial planning phase has been completed.
• Learned about of Internet of Things (IoT) and how it collects and exchange data through PLC/Sensors.
• Familiarization of Inductive Automation – Ignition software
• Familiarization of components such as Raspberry Pi module and noise sensor is done.
• Studied the basics of SCADA HMI , OPC
• Gantt chart prepared for the initial phase
• Minor thesis literature review and report is done

10) GANTT CHART:

Attachment:- Assignment Template.rar