PRE-COMMISSIONING USING DRONES FOR ANALYSIS OF AIR CONTAMINATION LEVELS IN SMART CITY

Contents

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Chapter 1 5

Introduction 5

Abstract 6

1. Introduction 6

2. Background study 7

3. UAV 8

4. Aim and objectives 9

5. Methodology and solution 9

6. Resources 10

7. Conclusion 10

Chapter 2 11

Literature Review 11

Introduction 12

Literature Review 13

Air monitoring system 13

Works related with water contamination 15

Finding from literature review 15

Chapter 3 17

Methodology 17

Abstract 18

Problem statement 18

Objectives 18

Methodology 18

Conclusion 24

Chapter 4 25

Feasibility study 25

Introduction 25

Feasibility analysis 26

Rules to fly drones in UK 27

Additional regulations for the drones with cameras 27

Legal feasibility 27

Operational feasibility 28

Economic feasibility 28

Technical feasibility 28

Risks for the drone monitoring system 29

Conclusion 29

References 30

Chapter 1

Introduction

Abstract

Air and water pollution is one the main issue for the environment and human. It is important to control the air and water pollution to protect the environment from climatic changes, global warming as well as protect human from various health hazard. Smart city is the application of IoT which collects data from people as well as various physical sources, environment from the city to take decisions for the health and quality life. The research will make use of UAV or drone to detect criterion air pollutants in the city as well as its source through sensors and GPS a system. The collected data will be analysed further and taking decisions.

1. Introduction

Air contamination refers to release of pollutants into the air that affect the health of human as well as the environment. Due increasing high transportation, as well as industries, may lead to air pollution through burning of fossil fuel. Vehicles use fossil fuels such as petrol, diesels which release carbon dioxide, sulphur as well as other green gases that are affecting the environment in terms of climate changes and global warming. Air pollution is also posing serious long term and short term health problems for human such as respiratory and cardiovascular diseases, damages of cells in the respiratory system, asthma, emphysema, bronchitis as well as cancer. Preventing and controlling air pollution is an important for the environment and human. Pollutants can occur from various sources like anthropogenic and natural. It can be classified into toxic and pollutants criterion. The following pollutants include the pollutants criterion such as Sulphur dioxide-SO2, Particulate material -PM10 & PM2.5, Nitrogen dioxide- NO2, Lead -Pb, Carbon monoxide -CO and Ozone -O3.

It is important to reduce the pollutants concentration in the atmosphere for saving the environment. Different techniques and methods have been used to detect the possible sources of emission for pollutants which includes fixing of remote stations in specific areas and mobile stations. Fixed terrestrial based techniques have limitation due to the lack of height adjustments for collecting pollutants. It is difficult for the terrestrial- based techniques for efficiently capturing the source of pollutants. Traditionally, aerial -based techniques make use of helium balloons and surveillance system. The system has the following risk factors like clashes, fire, physical damages etc.

The proposed project will resolve the issues associated with the terrestrial and aerial mobile methods through the U-Unmanned A-Aerial V-Vehicle-UAV or drones. It is an aircraft system which is operated by a human remotely or by an autonomous on board computer. It fixes with sensors for collecting the pollutants criteria as well as sends data to the ground station for further processing. The ground station will communicate with the web server to broad the data. The cost of the proposed system will also be reduced due to the open- source system of software and hardware.

2. Background study

The following concepts are involved in the research study such as

Smart city

Smart city is referred as the ability for integrating various technological solutions in a secure manner for managing the assets of the city which includes schools, libraries, hospitals, power plants, law enforcement as well as other community services. The main objective of the smart city is for improving the quality of life with the efficient use of technologies and data. The sustainability challenges of the city can be solved using efficient technologies and the data through improving health, air quality, energy use as well as transport. Smart city make use of innovative technology to create controlled environment for leading quality life in the city. The core idea of the smart city is the collection of data from citizens as well as objects and processing those data to retrieve useful knowledge which will be beneficial for the society and individuals. The technology uses sensors, detectors, wireless technologies, networking technology for data collection and communication. It uses I-information and C-communication T-technologies-ICT for enhancing the quality of life, improving productivity, performance. It also reduces cost as well as resource consumption and improving contact, which other for making effective decisions. It achieves the following benefit such as

• Improved economy
• Smart people
• Efficient management
• Effective communication
• Safe environment
• Improved quality of life

U-Unmanned A-Aerial V-Vehicle-UAV

It is a flying robot which is controlled by human remotely or autonomous on board computer through a software application. The aircraft does not carry operator on board which uses aerodynamic forces to fly in the air which can be retrievable as well as carry load. In IoT, it fixes with sensors and detector to gather details about the destination and sends data to the ground station. The features of UAV or drone as follows:

• Ability to fly in the air through aerodynamic force
• It can be piloted autonomously through a software program or human remotely
• Reusable and can carry loads

IoT

I-Internet o-of T-Things is the main backbone for the smart city in which things are connected over the internet for performing specific tasks. IoT connects physical devices for communicating as well as sharing data. The data are processed with efficient data analysis and decision making algorithms for taking decisions in real-time.

Data collection system

Data are collected from the real-time environment in IoT through sensors. It has data in the form of analog signals which will be converted into a digital signal for processing in the computer. Various components are involved to achieve the above tasks such as

• Sensors

Nowadays, sensors play an important role for sensing the real-time data from the environment. It can be used with various devices such as wearable, smartphones, health devices and so on. Sensors are an important component in IoT. It can monitor human health, quality of air, security of home and also used in I-Industrial I-Internet o-of T-Things –IIoT for monitoring protection etc.

It is a small device which detects the changes in the environment. While using the sensor with the electronic devices, it can capture pressure, temperature, moisture, humidity and so on. It transforms the captured signal into digital signals. Various sensors exists in the market for detecting the environment such as

• Pressure sensors
• Light sensors
• Motion sensors
• Gas sensors
• Gyroscopes
• Accelerometers
• Thermometers

The properties of the sensors are sensitivity, resolution and range. It can be classified into various categories such as active, passive, analog as well as digital.

3. UAV

More advancement has been done in the air pollution monitoring system. This section discusses the important advancement for preventing air contamination with UAV. Intel IoT Joint labs of china (Cheng et al 2013). In which group of researchers have developed the system for monitoring pollutants in the air those are hazardous for human health. The system which includes miniPAM that connected with the smartphone via GPS as well as attached with the UAV. MiniPAM collects data from the air along with GPS and transmitted to the server through 3G communication. The drone either operated from the ground through human or self-operating with pre-programing. Research centre Taiwan developed Lightweight remote-controlled W-whole A-air S-sampling C-component –WASC (Chang et.al. 2015) to monitor the pollutants in the air. UAV multirotor is integrated for gathering air sample from the chimneys those are in a tunnel of Hsueshan. The system uses mechatronic compose of a cylinder, electro valve as well as remote control for gathering data with two modes such as air extraction with pump via tub filled with the area absorbents and collection of air through vessel disposed through sampling pipe for analysis. The disadvantage of the system is, it collects only field samples as well as data to be analysed with the specialised laboratory for further interpretation. Another research project carried out in Italy, such as P-Photogrammetry for E-Environmental M-monitoring (PEM) to monitor the contamination in soil. In this system, cameras attached with the UAV for performing programmed trajectories on a specific area for getting camera shots. The data further analysed in the laboratory with the data analysis technique (Capolupo et. al. 2015).

4. Aim and objectives

Detecting air and water contamination is important for improving the quality of air through controlling the sources of air and water contamination. Fixed ait monitoring system cannot capture high concentration of pollutants in the air. Mobile-based aerial system is efficient for a detecting high concentration of air pollutants and its sources. For the smart city, it is one of the innovative measures to detect air pollutants in the environment and its sources. The proposed air and water contamination monitoring system includes UAV or drone with sensors for detecting the criterion air pollutants with improved coverage area. The gathered data will be transmitted to the server for further processing as well as which will be useful for effective decision making.

5. Methodology and solution

The proposed architecture of the “Analysis of Air contamination using UAV” is depicted below:

The UAV is attached to pollution sensors to collect criterion pollutants from the environment. The sensor sends the data to the controller of the IoT environment which sends data to the server. The locations of the pollutants are gathered through the GPS monitoring. Server process the data which evaluates whether the collected data.

6. Resources

The monitoring unit required the following components such as

• UAV S500 Tarot quatcopter
• Senor for measuring air quality
• Arduino card mega 2560
• XBee PRO S2B Antenna
• XBee antenna connection shield

Components for control station

• Computer
• Arduino mega board 2560 connected with xbee antenna
• 3DR receiver antenna

7. Conclusion

The report includes the proposal for the “PRE-COMMISSIONING USING DRONES FOR ANALYSIS OF AIR CONTAMINATION LEVELS IN SMART CITY”. It includes the project objectives, detailed project plan as well as resources required for the project.

Chapter 2

Literature Review

Introduction

Contamination is important considerable issue for the environment as well as human. Air pollution leads to environmental challenges as well as health hazardous. Green houses are the key responsible sources for global warming which absorb radiation from the sun. It will lead to global warming. Human activities such as burning of fossil fuels increase the concentration of greenhouse gases in the air. Global warming affects the ecosystem as well as biodiversity. By knowing the adverse impact of air pollution, various developing and developed countries are start taking remedies. One such remedy is using electrical vehicles. Electricity is renewable energy which does not burn any fossil fuels as well as does not release pollutants. Another technique is based on monitoring system. With the advancement in IoT, sensors are utilized to collect the data from the environment. In addition to the fixed system, sensors are also attached with mobility devices such as drones to gather data from the air at various altitudes. In smart cities, drones can be utilized to capture the air contamination as well as it source.

Like air contamination, water pollution also has got reasonable attention. Quality of water is essential for drinking as well as household purposes. It is also play an importable role in food production, power generation, recreational activities and fisheries. Polluted water lead to health issues for the human. High quality water is important to improve the socio economic development of country. Water pollution is caused due to the physicochemical as well as biological contamination. Physiochemical contamination occurs due to the chemical components those are released from industries. Biological contamination occurs due to the animal as well as human activities. Preventive as well as corrective methods are more useful to reduce contaminations.

Biological water contamination can be prevented through treatment process as well as proper management. Physiochemical contamination can be prevented only through strict monitoring. The water contamination is caused by improper maintenance, operation and quality control.

Various research works have been carried out to monitor water and air contaminations. UAV based research got more attention recent years. The research work will propose UAC monitoring to find the contamination. It is based on Quadcopter which is equipped with sensors as well as microcontrollers. The UAV has two system such as water and air quality monitoring system.

The air quality monitoring system can able to monitor the concentration of GHG’s such as methane-CH₄, carbon dioxide CO₂, water vapor -H2O, ozone -O3 at various altitudes. The monitoring system for water quality can able to collect water samples as well as detects the quality of water. The system will be beneficial for the Nigeria cities. Water ground is the main source for water. The system will be able to send data to remote monitoring station as well as can bale to store the data in SD card.

The research paper is based on the following structure such as methodology, components and its cots, results and conclusion.

Literature Review

The section presents the different existing works related to the proposed research work. It analyses the advantage and disadvantages of the existing system. UAV based monitoring system has got attention in recent years. It can be used for various applications such as agriculture, protection for environment, public safety, management of disaster and scientific researches. The system will save cost, lives as well as resources. Commercially available UAV can be used for monitoring the environment.

Air monitoring system

Radio controlled aircraft has used for monitoring the plantation growth in corn filed (Raymond et al 2003). The system has infrared camera for capturing images from the field. Based on the images, the system calculates the N-Normalized D-Difference V-Vegetation I-Index –NDVI which is used to measure the growth of the plantation. Greenhouse gases are captured through the system (Molnár1 2015) which has carrier device, software program and system to measure. The system monitors the air at low altitudes such as 500m from ground. It measures the parameters from the air such as temperature, humidity, radiation, dust, chemical pollution. It supports data processing for obtaining immediate details of the changes in air pollution over period of time. The collected data sent to the ground station to producing 3D images to illustrate the level of pollution.

Many research works use fleet of UAV rather than single UAV (Acevedo et al 2013). Heterogeneous UAV with limited range of communication has been adopted for detecting pollutions over large area. In this work, the observation area is divided into small areas and UAV collects data from each sub areas frequently. When the pollution is encountered then it will be informed to the entire fleet. This type of decentralized approach has been ensured through simulation as well as pre-determined patrolling strategies.

The authors work (Kingston et al 2008) is based on multiple UAV with decentralized approach. The system used for perimeter surveillance. It can be used for various applications such as bush fire detection. The authors investigated two type of perimeter topologies such as circular and linear. Authors concluded that, most of the works in the literature based on circular method. The system gathers data from all points of perimeter and sends that data to the base station for further analysis. For enhancing the surveillance UAV is flown uniformly over the perimeter area. Distributed algorithm used for collecting the data constantly and maintenance of uniform space between the UAVs.

The authors (Maza et al 2011) proposed autonomous surveillance system which has wireless actuator/sensors network, camera network. The aim of the work is for providing actuation capability involving various aerial and ground robots. The system has been designed based on task allocation/decomposition, resolutions for conflict, fusion of sensor data. It achieves the following requirements such as easy way of integration and robustness. The system mainly designed for accomplishing the following missions such as surveillance, confirmation for fire, tracking of fire-fighters and transportation of load.

The authors (Viguria et al 2010) proposed system for coordination ground as well as aerial robots. The system is mainly designed to surveillance as well as emergency management. Authors concluded that allocation of task is important strategy for this kind of application. The system makes use of the algorithm S+T which is D-distributed M-market based A-algorithm (DMA). The algorithm enables the robot to provide transportation as well as communication services to other robots dynamically. The authors demonstrated the communication of heterogeneous robots such as ground and aerial for detecting and extinguishing fire.

The authors (Laliberte et al 2018) adopted UAV for mapping the rangeland, assessment as well as monitoring. The UAV has equipped with GPS for capturing images from rangeland. The system has two UAV such as one of the UAV is modified airplane model which can fly through preloaded waypoints for acquiring images. The next UAV is autonomous flight which is equipped with digital camera as well as colour video. Both UAVs can fly up to 150m height. Image processing algorithms have been applied on those collected images for gathering useful information from it. The proposed system is cost effective.

Authors (Sidek et al 2014) presented prototype system to detect greenhouse gases. The UAV used to collect data from various nodes. The system used ZigBee technology for wireless communication. The air quality parameters such as O2, CO2, humidity and temperature are computed through the micro controller ATMEGA 328P. The computation performed on real time basis. Every 30 seconds, the system collects data and store in SD card. The data can be collected from various node. The system produced high accuracy.

Authors (Malaver et al 2015) proposed solar powered UAV system. It detects the greenhouse gases in agriculture land and transmits the data to the base station using W-wireless S-sensor N-network (WSN). It uses the generic gas sensors for detecting the gases CO2 and CH4. The main advantage of the system is the usage of solar power which is eco-friendly. Using the WSN it sends data to operators as well as external users. Authors tested the system for collecting as well as processing the data. Further analysis on the data will be done by the central node which produces 3D maps. The map shows the spatial as well as temporal distribution of CO2 and CH4 in the agricultural land.

The concentration of Methane in the atmosphere has captured using the small drone (Hugenholtz et al 2018). The system equipped with the detector of Methane gas which is cost effective. The system implemented in the companies such as B-Boreal L-Laser I-Inc (BLI) and V-Ventus G-Geospatial I-Inc (VGI).

Authors (Roldán et al 2015) used four rotor mini UAV with sensor system. The objectives of the work are for measuring the carbon dioxide concentration, temperature, luminosity and humidity and producing maps for the parameters. Authors have designed the system with careful consideration of the dynamics of quadrotor. Authors tested the system with real environment. From the work authors concluded that, Quadrotor produces high accuracy.

Works related with water contamination

The vehicles those are used for detecting the quality of water are S-surface V-vehicles (SV) and U-Underwater V-Vehicles (UV). Authors used surface vehicles for their research work (Dunbabin et al 2009). The system can able to navigate through the inland storage of water and measure the quality and emission of greenhouse gases. It equipped with L-laser based O-obstacle A-avoidance S-system (LOAS) and V-vision based I-inspection S-system (VIS) for navigating through the inland sources of water.

Authors demonstrated underwater vehicles (Cruz et al 2008) (Melo et al 2012). The vehicles can go down up to 100 m depth for monitoring the contamination through collecting and capturing video. Authors (Rahimi et al 2004) presented NIMS system for detecting the pollution of water. It follows S-semi M-mobile S-sensor (SMS) networks as well as supports A-adaptive S-sampling (AS). It can navigate through long distance. The demerits of the system are time consuming and expensive.

The work (Ceong et al 2007) collects the following parameters from the water such as D-dissolved O-oxygen –DO, T- total D-dissolved S-solid –TDS and temperature through sensors. The system will collect the data from the water and sends the data to the base station. When the parameter exceeds the normal range, it will send alarm to the user.

The SMS based system proposed to monitor the quality of water from remote location (Mohd 2007). Two parameters are captured from the water such as pH and D-Dissolved O-Oxygen-DO and stored in the system. It uses GSM network.

Authors (Aquacopters 2020) used Aqua-copter to measure the quality of water. The UAV used in the system can land in as well as takes off from calm water surface. The demerits of the system are difficult to take off from the fast flowing water surface.

Finding from literature review

From the literature review, the following details are observed:

• Existing UAV system equipped with complicated sensors as well as instrument.
• Implementing of greenhouse gas monitoring system on these devices are expensive
• Systems are difficult for installing. It needs professionals for installing as well as configuring the system
• End users difficulties for using the system. The interfaces are not user friendly
• Non customization of system. The systems cannot be customized based on the user needs
• Most of the existing water quality monitoring system has manual work. It needs human to collect water samples from the sources. The collected samples are tested in lab and results are stored for further analysis
• Manual work consumes more time and lead error
• Due to time consuming for producing the result, it will also postpone the corrective actions.

Chapter 3

Methodology

Abstract

The research work proposes reliable as well as low cost air and water contamination monitoring system. The proposed system uses equipped with UAV- U-Unmanned A-Ariel V-Vehicle which includes sensors, microcontroller and wireless system. The proposed system has air and contamination monitoring system which has gas and water quality sensors as well as microcontroller. It measures the green house air concentration at various altitudes with various environmental conditions. Through water quality sensors, water samples are collected from on and off shore. The proposed system has the capability to store the collected data in on board SD card. The sensors are also sending the data to the monitoring system which exists in the ground through wireless communication. The system will be reconfigurable as well as upgradable.

Problem statement

Accurate detection of air and water contamination is essential for leading healthy life. Smart cities take initiatives through technologies for detecting the contamination of water and air. The accurate detection of those contaminations will helpful for taking mitigation strategies for controlling as well as preventing such contamination. Existing approaches use UAV system to detect the contamination in the environment. The drawbacks of the existing solution are complex to install and configure as well as expensive. It is essential to design and develop more user friendly and cost effective system to detect greenhouse gases and water contamination.

Objectives

The research work proposes reliable as well as low cost air and water contamination monitoring system. The objective of the research work is to provide the possible solutions and methodologies to monitor air and water quality in smart city. It also conveys the expected deliverables from the project. The research work also illustrates the design and development of proposed drone monitoring system for the smart city. It also includes the feasibility study related with different stakeholders.

Methodology

The section shows the methodology of the system and component of the system. The proposed system will include the following components such as

• UAV
• System to measure quality of air
• System to measure quality of water

UAV

U-Unmanned A-Ariel V-Vehicle –UAV is built using the light composite materials for reducing weight of the aircraft as well as increasing manoeuvrability. The composite materials are useful for the UAV to fly at high altitudes. UAV drones are built with various technologies such as GPS, laser, infrared cameras. It can be controlled from the ground. The system is known as G-ground C-control S-system-GSC. It is also known as cockpit.

UAV has two main components such as drone and control system. UAV is equipped with sensors for detecting the environment. The materials used to build the small aircraft absorb vibration which reduces the sound produced. The materials used on UAV are light weight.

The proposed work makes use of Advanced model of Phantom 3 for UAV. The below table shows the necessary parameters of UAV. The features of UAV will be used for the project. Example of such feature is, it can fly to remote places.

Specification of UAV

S.No	Parameters	Values
1	Weight (inclusion of battery and propeller)	1280 gm
2	Ascent speed (maximum)	5 m/s
3	Descent speed (Maximum)	3 m/s
4	Max. Speed	16 m/s (Mode: ATTI and no wind)
5	Flight altitude (Maximum)	6000m
6	M-Maximum R-Right T-Time-MRT	23 min
7	O-Operating T-Temperature-OT	0 to 400c
8	GPS mode	GLONASS/ GPS
9	Range of control	Pitch : -90o to 30o

The Phantom 3 Advanced model has intelligent flight mode. The model enables the UAV for auto take off and land. The can be controlled using the smart device. The position aircraft can be tracked on map. It will be used to set new home point. UAV can capture video as well as shots.

Phantom 3 Advanced model drone is depicted below:

The Phantom 3 advanced model achieves better range, quality of video streaming as well as reliability than other models. Lightbridge is the technology which is used in Phantom 3. It will be useful for handling video as well as control signals. In good weather condition, the technology allows the aircraft to travel more than 5000m from pilot. The UAV of Phantom 3 Advanced model can travel four times longer than other technologies. It has various features such as holding of GPS position, follow me, waypoints, point of interest, home lock, course lock, return to home, real time monitoring of battery, estimation of flight time, photo and video stabilization, manual control for the camera exposure. It avoids obstacles. The system has two cameras such as one camera is for recording video and other camera is for stabilization. Moving shots can be captured using the moving stick of the controller. The moving stick of the controller is used for the new pilot for assisting the aircraft without any jerking.

Greenhouse monitoring system

The measurement system for gas has controller which is based on monitoring unit mounted on Quadcopter. The below diagram shows the gas measurement system:

The monitoring system for gas has micro controller unit, wireless unit, storage devices and sensors.

Microcontroller

The proposed research work will make use of Arduino micro controller due to its various features. It is prototype platform for easy to use software and hardware. It has circuit board which is programmed (microcontroller) as well as readymade software Arduino IDE. The I-integrated D-development E-environment (IDE) is using to write as well as upload code for the physical board.

It has the following features such as

• Arduino can able to read both digital as well as analog signals. It can read signals from various sensors and convert the received signals into output in the form activating motor, turning on/off LED as well as connect to the cloud
• Arduino board can be controlled through sending signals to the microcontroller from the IDE of Arduino
• It does not need additional hardware or programmer need not do any additional coding for the board
• It needs only USB cable to use
• Integrated Development programme uses C++ language which enable the programmer to learn the program
• It breaks functions of micro controller
• Easy for finding compatible hardware in market
• Simple for integrating with other software as well as hardware
• Easy for creating user friendly interface

Wireless technology -Zigbee

Wireless networks as well as sensors are more important for efficient monitoring as well as controlling the system. Wireless technologies are used to sense, transfer as well as control in gas monitoring system. The proposed work will use ZigBee technology. Zigbee wireless technology is more efficient than other wireless technologies. It consumes low power. It provides communication for long range devices. The protocol Zigbee has various features such as

• Offers support for different network topologies such as P-Point – 2-to –P-point (P2P), P-point – 2- to M-multipoint- P2M, mesh network
• Provides long life for battery
• Low latency
• D-Direct S-Sequence S-Spread S-Spectrum –DSSS
• Network can have 65000 nodes
• Follows AES encryption -128 bit for secure data communication
• Avoids collision, retries as well as acknowledgments

The architecture of zigbee is illustrated below:

Sensors

The air quality data can be collected using sensors. It is used to sense gases as well as their concentration. It transforms changes of physical quantity into the electrical signals. Switching circuits are integrated with sensors. Circuits can operate through the signals. The sensors as well as switching circuits are continuously operating in the proposed system for real time monitoring. The measured data will be recorded into the S-storage D-device-SD. It enables efficient as well as accurate A-air Q-quality M-monitoring (AQM) system in specific location where links of wireless communication broken or weak.

The proposed work will have two modes for the management of data. The UAV can be controlled either manually or automatically. In automatic operation the waypoints are fixed prior. These waypoints are mentioned in the map. UAV follow the waypoints defined in the map and measures the quality at various locations in the way at various altitudes. The collected data will be stored in the SD card. For two minutes, UAV stays in one location. After that, it will be flied to the next location. After completing its mission, it will return back to home place (origin). The flow chart for the air quality monitoring system is depicted below:

Gas monitoring system will have the following units such as

• Gas sensors such as CO₂, O₃, CH₄.
• Humidity and temperature sensor
• Humidity and pressure sensor
• Storage device card module

Lightweight, compact as well as low power sensors will be used in the proposed work to measure the air particles in the atmosphere. The sensors are specifically designed for the applications of UAV. The overall weight of the sensor will be 200 gms with the inclusion of batteries. The consumption of electric energy for each sensor will be 2W. Sensors can be operated through the energy received by the batteries. L-Laser A-absorption S-spectroscopy (LAS) based measurement technique used by the sensors. The technique follows low power V-vertical C-cavity S-surface E-emitting L-laser –VCSEL in near infrared spectral region. The technique operates with 5 to 10 mA of current as well as 5V power supply for scanning the absorption features of the gaseous particle in the region. Laser is operated from T-thermo E-electric C-cooler -TEC module, T-Thorlab VTC-VTC002 D-diode L-laser (TVTCDL) current driver, electronic board for sweep as well as modulation. XR2206CP is used to develop laser current ramp and sine modulator. Each sensor is sensitive for its specific gas concentration. The senor MQ 135 is used to sense carbon dioxide, MQ 131 used to sense O₃ and MQ 4 is for CH₄.

Air monitoring system of the propped research work is depicted below:

In addition to the above three gas sensors, two more sensors such ad temperature & humidity DHT11 and pressure & Altitudes (BMP 180) are also used. The sensor DHT 11 produces 5% accuracy over the temperature 0 to 50 ⁰C. The sensor BMP 180 achieves accuracy 2% over humidity 20% to 80%. It will sense from 900m to 500m above sea level as well as with the resolution (0.03hPa / 0.25m). in the proposed research work, sensor BMP 180 will be used as temperature sensor.

Conclusion

The research proposal is proposed to monitor air and water contamination in smart. The research work proposes reliable as well as low cost air and water contamination monitoring system. The proposed system uses equipped with UAV- U-Unmanned A-Ariel V-Vehicle which includes sensors, microcontroller and wireless system. The proposed system has air and contamination monitoring system which has gas and water quality sensors as well as microcontroller. It measures the green house air concentration at various altitudes with various environmental conditions. Through water quality sensors, water samples are collected from on and off shore. Contamination of water and air will be analysed using the drone monitoring system.

Chapter 4

Feasibility study

Introduction

Drone monitoring system play vital role in smart cities that are highly interconnected with advanced technologies. Drone play an important role for smart cities which enhance the life style of smart cities. It will helpful not only for the current practices in smart city nut also provides new opportunities for improving their environment, economic and operational development. Drone will be helpful for any residents of smart city to prepare for modern era. It is used for different applications such as package delivery, traffic monitoring, police system, drone taxi, ambulance drone, and pollution as well as control firefighting system. The research work concentrates on drones for environment monitoring to control air and water pollutions.

Feasibility analysis

Feasibility study is important for every project before it will start implementing. It will be conducted with different factors such as economical, technical, legal, financial and operational and so on. It will convey whether the project is feasible to implement or not (Melo et al 2012).

It will provide high quality up to date details about the environment such as air quality and water quality to the operational planners as well as controllers for directing resources when alarm detected from the environment. The research is focused on drone monitoring system for leeds in West Yorkshire. The city of Bradford Metropolitan District council is aiming to use emerging technologies for supporting local goals such as healthy and safe communities. While considering the drone technology for the city, local stakeholders expect the benefits from the project.

Monitoring as well as managing the quality of water and air is important for city management. Most of the people are living in cities. While increasing the pollution in water and air will lead serious health issues for the people who live in that city (Rahimi et al 2014). The research project is proposed to monitor the pollutant particles in air and water for the West Yorkshire city.

The real time monitoring system for the city will helpful for the people to increase their life time through living in safety and healthy environment.

Air and water monitoring system with drones can be divided into different phases such as

• Planning

• Providing up to date high definition map as well as model of each site
• Enhance map and model with other data sources as well as data points like location of pollutants, utility location and so on

• Response

• Observe the specified site in terms of air and sources of water
• Identification of site and water source is at risks
• Recovery
• Assessing and helping the site to recover more quickly

Drone monitoring system offers the following benefits:

• Reduced GHG emissions
• Improved air quality
• Better support for water conservation
• Detecting leakages

List of stakeholders for the research

• Public
• Government
• Industries
• Network provider

Rules to fly drones in UK

To place drone in UK, the drones should be under the weight of 20 kg. It should not go beyond 400 feet height as well as 500 meters horizontally from the operator (Ceong et al 2007). The drone should always be in the control of operator. It should not disturb the helicopters, aircraft as well as airfields. The aircraft should be fly with high security. When the weight of the drone exceeds the 250 grams that must be registered with CAA. Both drone as well as operator should get ID. It should be flown within 50 m of building, vehicles, people and vessels. It should be flown within 150 m of large group of people, congested area, and sports area. Before placing the drone on specific area, it is important to must inform to the people about the drone monitoring system. It is required to respect privacy and security of people (Nottinghamshire et al 2020).

Additional regulations for the drones with cameras

Drones should not be flown within 50ms of vehicles, people, vessels and buildings. It should be flown within 150 m of large group of people, congested area, and sports area. Before placing the drone on specific area, it is important to must inform to the people about the drone monitoring system. It is required to respect privacy and security of people.

Legal feasibility

For using the drone to monitor water and air, it must be register as well as has to get flyer ID. The person is responsible for the drone or model the aircraft has to register as well as get operator ID. While placing drones for smart city, it can be possible to register the drone as well as responsibilities to get operator ID. While analysing the water resources, it must be informed to authorized person to analyse the water resources. Legally the drone monitoring is feasible after getting approval from CAA, local authorities and local people and other stakeholder of the project.

Operational feasibility

Drones or U-unmanned A-aerial V-vehicles (UAV) are machines that controlled by human remotely from the ground. More number of drones are used nowadays to enrich the life style for people. It also improves the safety and security of people.

C-Civil A-Aviation I-Industry-CAA offers guidance to use drones for both commercial and private purposes. The drones should be less than 20 kg weight and it should not go beyond 400 feet height as well as 500 meters horizontally from the operator. The drones used for monitoring the environment will be less than the weight of 20 kg. It is possible to place multiple drones and multiple control station in city to constantly monitor the drones.

It is enough to get the pollutant below the height of 400 feet from the earth surface. The drone monitoring system also fulfils the operational feasibility.

Economic feasibility

Sensors are available at cheapest prices. Sensors are available at the affordable prices. Drone monitoring system offers various benefits for the city which includes safe and healthy environment, economic development, and extension of life time and so on. Befits of the project are high while comparing the cost incurred for the project with the benefits. Based on cost benefits analysis, the project is feasible.

Technical feasibility

The following is the proposed specification for the UAV:

S.No	Parameters	Values
1	Weight (inclusion of battery and propeller)	1280 gm
2	Ascent speed (maximum)	5 m/s
3	Descent speed (Maximum)	3 m/s
4	Max. Speed	16 m/s (Mode: ATTI and no wind)
5	Flight altitude (Maximum)	6000m
6	M-Maximum R-Right T-Time-MRT	23 min
7	O-Operating T-Temperature-OT	0 to 400c
8	GPS mode	GLONASS/ GPS
9	Range of control	Pitch : -90o to 30o

The mentioned specification follows the rules and regulations for placing drone in UK. Low cost sensors are available to capture the Greenhouse gases and sensors are available equipped with water collecting components and sensing unhealthy water particles. Drone can be connected with the base station to send collected data details through wireless communication technologies. Zig bee is one of the effective wireless communication technology. According to this study, the prosed drone project also satisfies the technical facility.

Risks for the drone monitoring system

The following are the challenges related with drone monitoring system such as

• Safety

While deploying drone in highly dense areas may lead to various safety issues for the drone. There is possibility to get damage due to crashes. The crashed drone will malfunctions. Improper maintenance, mis-use by the operator and collision of mid-air lead to safety issues for the stakeholders. Poor weather conditions, lightening, turbulence are also triggering fall of drone on public properties. Sharing the space in air with other commercial aircrafts lead serious risk of collision (Mohd et al 2007).

• Security

The security concern related with drone system is due to the technology which is used on the drone. The technologies may be destroyed or hijacked by the cyber criminals. Drone navigation as well as communication are vulnerable for various security breaches. Drone with GPS are highly vulnerable for security breaches due to its unencrypted as well as unauthenticated nature of communication. Jamming of Wi-Fi is another risks related with drone communication. It also leads to severe challenges for the nearby people.

• Privacy

Privacy is serious risk related with drone monitoring system. Drones follows various agile access method which is different from other gadgets. Drone system contain sensitive data like sensor data, captured images from camera and so on. It leads a very big privacy concern when the sensitive data hijacked or access maliciously.

Conclusion

Contamination is important considerable issue for the environment as well as human. Air pollution leads to environmental challenges as well as health hazardous. Green houses are the key responsible sources for global warming which absorb radiation from the sun. It will lead to global warming. Human activities such as burning of fossil fuels increase the concentration of greenhouse gases in the air. Global warming affects the ecosystem as well as biodiversity. By knowing the adverse impact of air pollution, various developing and developed countries are start taking remedies.

Drone monitoring system which enriches the people life style. It provides more innovation solution for different environmental issues like air, water contamination etc. Most of the people are living in cities. Air and water quality management is important in smart cities. The system can be detect the contamination of water and air and which is helpful to proper strategies to control the contamination. The research report performs detailed literature review. It also proposed methodologies to implement the drone monitoring system and also provides plan for conducting feasibility study.

References

• Cheng, Y., Li, X., Jia, J., Zhang, J., Lin, K., Liu, X., Li, Y., Jiang, X. (2013). An autonomous aerial system for air-quality surveillance and alarm. J. China Intel IoT Joint Labs. 13, pp. 491–492
• Chang, C.-C., Wang, J.-L., Chang, C.-Y., Liang, M.-C., Lin, M.-R.: (2015). Development of a multicopter-carried whole air sampling apparatus and its applications in environmental studies. Chemosphere 144, 484–492
• Capolupo, A., Stefania P., Collins O., Nunzio F., Lorenzo, B.: (2015). Photogrammetry for environmental monitoring: the use of drones and hydrological models for detection of soil contaminated by copper, ScienDirect, University of Naples Federico II, Department of Agricultural Sciences, via Università 100, 80055 Portici Naples, NA, Italy

• Raymond H.E., Daughtry C. S.T, Walthall C.S., McMurtrey J.E., Dulaney W.P., (2003). “Agricultural Remote Sensing using Radio Controlled Model Aircraft”, Digital Imaging and Spectral Techniques: Applications to Precision Agriculture and Crop Physiology, ASA-CSSA-SSSA, Madison, WI, pp. 197–205.
• Molnár1 A (2015)., “A Multi-rotor System for the Collection and Analysis of Measurements to Evaluate and Spatially Demonstrate the Pollutants in the Air”, International Journal of Advanced Robotic Systems, 12:187 https://doi.org/10.5772/61229
• Acevedo J. J., Arrue B. C., Diaz-Banez J. M., Ventura I., Maza I., Ollero, A (2013).., “Decentralized strategy to ensure information propagation in area monitoring missions with a team of UAVs under limited communications”, Unmanned Aircraft Systems (ICUAS), 2013 International Conference on, pp. 565–574, Available at http:/doi.org/10.1109/ICUAS.2013.6564734
• Kingston D., Beard R. W., Holt R (2008)., “Decentralized perimeter surveillance using a team of UAVs”, Robotics, IEEE Transactions on, Vol. 24, No. 6, pp. 1394–1404, https://doi.org/10.1109/TRO.2008.2007935
• Maza I., Caballero F., Capitan J., Martinez-de-Dios J. R., and Ollero A (2011)., “A distributed architecture for a robotic platform with aerial sensor transportation and self-deployment capabilities”, Journal of Field Robotics, Vol. 28, No. 3, pp. 303–328, https://www.doi.org/10.1002/rob.20383
• Malaver A.J. R., Gonzalez L.F., Motta M., et. al, “Design and flight testing of an integrated solar powered UAV and WSN for greenhouse gas monitoring emissions in agricultural farms”, Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems, IEEE, Congress Centre Hamburg, Hamburg, Germany, pp. 1-6,
• Viguria A., Maza I., Ollero A (2010)., “Distributed service based cooperation in aerial/ground robot teams applied to fire detection and extinguishing missions”, Advanced Robotics, Vol. 24, No. 1–2, pp. 1–23, , https://doi.org/10.1163/016918609X12585524300339
• Laliberte A. S., Rango A., Herrick J. E (2018)., “Unmanned Aerial Vehicles for rangeland mapping and monitoring : A comparison of two systems”, Proceedings of the American Network Protocols and Algorithms ISSN 1943-3581 2017, Vol. 9, No. 3-4 54 www.macrothink.org/npa Society for Photogrammetry and Remote Sensing Annual Conference, Tampa, FL,2007, https://jornada.nmsu.edu/files/bibliography/07-033.pdf accessed on January 16,
• Sidek, O., Abdullah, A., Za’bah, U. N., Amran, N. A., Jafar, H., Hadi, M. A., … & Mansor, M. (2014, May). Development of prototype system for monitoring and computing greenhouse gases with Unmanned Aerial Vehicle (UAV) deployment. In 2014 International Symposium on Technology Management and Emerging Technologies (pp. 98-101). IEEE.
• Malaver Rojas, J. A., Gonzalez, L. F., Motta, N., Villa, T. F., Etse, V. K., & Puig, E. (2015, September). Design and flight testing of an integrated solar powered UAV and WSN for greenhouse gas monitoring emissions in agricultural farms. In 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (Vol. 1, No. 1, pp. 1-6). IEEE.
• Hugenholtz C., and Barchyn, T (2018)., “ A Drone in Search of Methane”, Project Summary – February 2016, University of Calgary available at http://ventusgeo.com/wp-content/uploads/2016/04/Project_outline_no_watermark-1.pdf accessed on January 16,
• Roldán J.J., Joossen G., Sanz D., Cerro J., and Barrientos A (2015).,” Mini-UAV Based Sensory System for Measuring Environmental Variables in Greenhouses”, Sensors, 15, pp. 3334-3350 https://doi.org/10.3390/s150203334
• Dunbabin M., Grinham A., and Udy J. (2009), “An autonomous surface vehicle for water quality monitoring,” Australian Conference on Robotics and Automation, Sydney, Australia, December 2-4, , vol. 13, 2009, http://www.araa.asn.au/acra/acra2009/papers/pap155s1.pdf
• Cruz N.A. and Matos A.C (2008)., “The MARES AUV, a Modular Autonomous Robot for Environment Sampling,” Proceedings of IEEE OCEANS, Quebec City, QC, Canada, September 15-18, pp. 1–6, https://doi.org/10.1109/OCEANS.2008.5152096
• Melo J. and Matos A (2012)., “Bottom estimation and following with the MARES AUV”, Proceedings of IEEE Oceans, Hampton Roads, VA, USA, October 14-19, 2012, pp. 1–8 https://doi.org/10.1109/OCEANS.2012.6404917
• Rahimi M., Pon R., Kaiser W., Sukhatme G., Estrin D., and Srivastava M. (2004)., “Adaptive sampling for environmental robotics,” Proceedings of the IEEE International Conference on Robotics and Automation, New Orleans, LA, USA, USA, 26 April-1 May, Vol. 4, 2004, pp. 3537–3544, https://doi.org/10.1109/ROBOT.2004.1308801
• Ceong H., Park J.S., and Han S (2007). “IT convergence application system for eco aquafarm”, Proceedings of the IEEE Frontiers in the Convergence of Bioscience and Information Technologies, Jeju City, October 11-13, pp. 878-883 https://doi.org/10.1109/FBIT.2007.75
• Mohd S.S (2007). “Intelligent Aquaculture System via SMS”, University of Teknology. Petronas, Malaysia,
• “Aquacopters.” [Online]. Available: http://www.aquacopters.com
• Melo J. and Matos A (2012)., “Bottom estimation and following with the MARES AUV”, Proceedings of IEEE Oceans, Hampton Roads, VA, USA, October 14-19, 2012, pp. 1–8 https://doi.org/10.1109/OCEANS.2012.6404917
• Rahimi M., Pon R., Kaiser W., Sukhatme G., Estrin D., and Srivastava M. (2004)., “Adaptive sampling for environmental robotics,” Proceedings of the IEEE International Conference on Robotics and Automation, New Orleans, LA, USA, USA, 26 April-1 May, Vol. 4, 2004, pp. 3537–3544, https://doi.org/10.1109/ROBOT.2004.1308801
• Ceong H., Park J.S., and Han S (2007). “IT convergence application system for eco aquafarm”, Proceedings of the IEEE Frontiers in the Convergence of Bioscience and Information Technologies, Jeju City, October 11-13, pp. 878-883 https://doi.org/10.1109/FBIT.2007.75
• Mohd S.S (2007). “Intelligent Aquaculture System via SMS”, University of Teknology. Petronas, Malaysia,
• www.nottinghamshire.police.uk › advice › drone-law-uk (2020)