AU2020102711A4

AU2020102711A4 - LoRa - Zigbee Hybrid Smart Communication System

Info

Publication number: AU2020102711A4
Application number: AU2020102711A
Authority: AU
Inventors: Anand Nayyar; Van Truong Truong
Original assignee: Individual
Current assignee: Individual
Priority date: 2020-10-14
Filing date: 2020-10-14
Publication date: 2020-12-03
Anticipated expiration: 2028-10-14

Abstract

ABSTARCT A system of monitoring smart cities, agriculture and underwater is disclosed. A plurality of sensor modules are wirelessly communicating with a mainframe server, wherein the sensor modules are configured to receive a input signal from the mainframe server when the mainframe server is turned ON, wherein the sensor modules are configured to detect a plurality of parameters upon receiving the input signal from the mainframe server and transmit the parameters to the mainframe server. An IoT interface module is coupled to the mainframe server at one end and to the sensor modules at the other end. A microprocessor control unit is communicatively coupled to the mainframe server through the IoT interface module, wherein the microcontroller receives input parameters from the different sensor modules. A cloud interface server is in communication with the mainframe server, wherein the cloud interface is configured to receive the parameters, detected by the sensor modules, from the mainframe server and store the parameters in a cloud storage module. A user interface is wirelessly communicated to the cloud interface, wherein the user interface transmits an input command to the cloud server, wherein the cloud server upon receiving the input command from the user interface, transmits the stored parameters from the cloud storage module to the user interface. 17 / MAINFRAME MICROPROCESSOR INTERFACE CONROL U QNITk IoT FIG.21

Description

ABSTARCT

A system of monitoring smart cities, agriculture and underwater is disclosed. A plurality of sensor modules are wirelessly communicating with a mainframe server, wherein the sensor modules are configured to receive a input signal from the mainframe server when the mainframe server is turned ON, wherein the sensor modules are configured to detect a plurality of parameters upon receiving the input signal from the mainframe server and transmit the parameters to the mainframe server. An IoT interface module is coupled to the mainframe server at one end and to the sensor modules at the other end. A microprocessor control unit is communicatively coupled to the mainframe server through the IoT interface module, wherein the microcontroller receives input parameters from the different sensor modules. A cloud interface server is in communication with the mainframe server, wherein the cloud interface is configured to receive the parameters, detected by the sensor modules, from the mainframe server and store the parameters in a cloud storage module. A user interface is wirelessly communicated to the cloud interface, wherein the user interface transmits an input command to the cloud server, wherein the cloud server upon receiving the input command from the user interface, transmits the stored parameters from the cloud storage module to the user interface.

/ MAINFRAME MICROPROCESSOR INTERFACE

CONROL U QNITk IoT

FIG.21

LoRa - Zigbee Hybrid Smart Communication System

FIELD OF INVENTION

The present invention generally relates to a field of electronics and communication engineering and particularly to the field of monitoring system. The present invention specifically relates to a smart monitoring system of agricultural production, city management system through different gateways and nodes of communication modules.

BACKGROUND OF THE INVENTION

The system of monitoring and technology over the past few years have seen a tremendous inclination due to the explosive growth of internet of things (IoT). The IoT applications have contributed significantly to many industries, such as automobile, agriculture, medical, and electronics. The trend of IoT (Internet of Things) has opened up many advantages for researching, building, and deploying intelligent networks worldwide, including sensor networks. Wireless Sensor Network (WSN) plays an essential role in this smart system. WSN is a collection of sensor nodes that use wireless links (radio, infrared or optical) to coordinate the implementation of large-scale distributed data collection under any conditions and in any location, any geographical region. Many communication protocols for wireless sensor networks have been developed, such as Bluetooth, Wi-Fi, BLE, Zigbee, LoRa, NB-IoT, and LTE-M. In particular, the two protocols Zigbee and LoRa, are attracting much attention in the world of research. However, most of the designs that come from academia and industry have shortcomings that need to be addressed.

A research article shows that the hardware model is deployed in the house with six measurement nodes simultaneously using a Zigbee network deployed by Arduino and XBee transmission modules. The parameters are collected and sent to the base station and stored at the server. The work presents environmental parameters in the form of visual graphs but has not focused on system protocol. Moreover, some noticeable disadvantages of this design are also listed as follows; design in the form of a circuit board made up of pairing discrete modules (Arduino Uno module, Xbee module, sensor module), not according to industry standards. It also leads to a problem when adjusting the sensor and challenging to apply in practice. The circuit board also limits the number of sensors connected, and these sensors are permanently mounted, so there is no flexibility. The disadvantage of the Zigbee communication protocol is that the coverage of each node is meager, it is difficult to expand the network size.

Specifically, some researchers have applied WSN in agriculture to save the water consumption. The sensor nodes will collect energy and transmit to the central data processing station via the Zigbee protocol. The central station will make the appropriate irrigation decisions and ensure water saving as much as possible. However, the system uses AC-DC adapter power to operate under AC power conditions, which is not feasible in practice.

Besides that some Zigbee node prototypes available in the market are not practically feasible to operate. They have different disadvantages, so they are challenging to use in a real environment. Some Zigbee module design is purely for the Zigbee protocol study and it does not contain any expander port, so it is impossible to connect with the sensor module. Some designs only support digital sensor types, meaning that only detects some events logically with or without, so they are not suitable for analog sensor modules or sensor modules which use protocol SPI, 12C. A relatively complete Zigbee node product only works within Zigbee coverage. Therefore, many repeater modules need to be deployed when expanding the system, so the system cost is very high.

To solve the problem of expanding the coverage of WSN another communication protocol LoRa based WSNs is applied to agriculture. The work describes how to design network nodes and server websites. The system can use many sensor modules, but using only the solar power will limit the system's uptime when it is dark, or there is not enough light. Furthermore, non-industry standard coupling boards can be energy consuming and challenging to perform calibration. A complete LoRa node can only operate in a LoRa system and cannot be compatible with other wireless networks. While in reality, there were a lot of Zigbee networks deployed, and it is impossible to replace these completely. Specifically, the combination of these two networks makes use of the available resources of the Zigbee network (developed since 2010) and expanded the coverage of the network using LoRa-WAN. A WSN model based on a combination of Zigbee and LoRa is also availabe. The system uses STM32 as the central processor, with the SX1278 module for LoRa communication and the Xbee Pro module for Zigbee communication. The above studies show that the interoperability between IoT wireless communication techniques is still quite limited.

Despite having many advantages such as energy efficiency, supporting mesh network topology, Zigbee technology has a significant downside such as; low-data-rate: Zigbee uses the IEEE 802.15 WPAN specification, providing data rates of 250 kbps, 40 kbps and 20 kbps; the coverage is quite limited. It only works in distances from 10 to 500 met line-of-sight. To extend coverage, it is recomended to install multiple Zigbee relay stations and/or increase transmit power. However, it leads to increase the installation and maintenance costs of the system. Moreover, this technology has been deployed in many systems in Vietnam and the world, especially in the field of Smart grid and Smart agriculture. It is not feasible to remove or completely replace these Zigbee devices. A similar problem occurs with Wi-Fi technology. The limited coverage makes the Wi-Fi Gateway only be installed locally, making it difficult in large-range surveillance applications. Meanwhile, in recent years, LoRa emerged as the most outstanding candidate who could serve WSN on a large scale. LoRa has excellent features such as low energy consumption, long-distance communication, and cheap equipment. However, LoRa still has its disadvantages, such as relatively low transfer speed and low data load. Some existing system such as US8296408B2 discloses a distributing relocatable services in middleware for smart items; and US10650622B2 discloses a monitoring apparatus provides vehicle telematics data.

Therefore a system is needed that combines these wireless communication technologies in a WSN system. Specifically, between the cluster networks, Zigbee and LoRa will be connected via the Zigbee-LoRa converter module. The present invention employs a LoRa-Wi-Fi gateway to transfer data to the server and ensures compatibility with existing Zigbee systems and integrates LoRa to solve coverage expansion in WSN at no extra cost and thereby to overcome the limitations and disadvantages of the existing technologies.

SUMMARY OF THE INVENTION

The present invention relates to a system for monitoring smart cities, agricultural lands on a large scale by employing a cluster of network module nodes in order to connect and communicate with various environmental sensors such as temperature, humidity, light intensity, CO concentration, LBG, pH, and liquid turbidity.

In an embodiment of the present invention a system of monitoring smart cities is disclosed. The system comprising: a plurality of sensor modules wirelessly communicating with a mainframe server, wherein the sensor modules are configured to receive a input signal from the mainframe server when the mainframe server is turned ON, wherein the sensor modules are configured to detect a plurality of parameters upon receiving the input signal from the mainframe server and transmit the parameters to the mainframe server; an loT interface module coupled to the mainframe server at one end and to the sensor modules at the other end, wherein the loT interface modules are configured to receive input signal from the mainframe server and transmit the received input signal to the sensor modules; a microprocessor control unit communicatively coupled to the mainframe server through the loT interface module, wherein the microcontroller receives input parameters from the different sensor modules, wherein the microcontroller processes the parameters and transmits to the mainframe server; a cloud interface server in communication with the mainframe server, wherein the cloud interface is configured to receive the parameters, detected by the sensor modules, from the mainframe server and store the parameters in a cloud storage module; and a user interface wirelessly communicated to the cloud interface, wherein the user interface transmits an input command to the cloud server, wherein the cloud server upon receiving the input command from the user interface, transmits the stored parameters from the cloud storage module to the user interface.

Another embodiment of the invention is that the system comprises a first sensor module configured to detect temperature and humidity with a calibrated digital signal output, wherein the module comprises a resistive-type humidity measurement element and a negative temperature coefficient (NTC) measurement element, wherein the first sensor module is connected to a microcontroller.

Another embodiment of the invention is that the system comprises a microprocessor coupled to the first sensor module, wherein the microprocessor is configured to transmit an input signal to the sensor module, wherein the microprocessor sets a signal pin as an output pin and controls the signal pin to a low level for a period of at least 18 meters, wherein the sensor module receives commands from the microprocessor in order to measure a value of temperature and humidity, wherein the microprocessor controls the signal pin to a high level, then resets it as an input pin. The microprocessor after a time period of 20-40 seconds, shifts the signal pin to a low level, wherein when the duration time is larger than 40us and the signal pin is not shifted down to the low level, the microprocessor does not communicate with the sensor module. The microprocessor signal pin for a duration of 80 seconds in low level is automatically shifted to a high level and when the signal pin is in the high level the microprocessor communicates with the sensor modules.

Another embodiment is that the system comprises a second sensor module configured to detect light, wherein the second module comprises a photodiode to receive an electric current and transmit the electric current to an operational amplifier in order to convert it into a voltage signal, wherein the signal is transmitted to an analog to digital converter to turn it into a 16-bit digital signal, wherein the sensor module measures a wide range (1 - 65535 lx) with adjusted resolution settings of 0.5 lx, 1lx, and 4lx, wherein the sensor module operates with 3 modes, low resolution mode, first high resolution mode and second high resolution mode.

Another embodiment is that the system comprises a third sensor module configured to measure soil moisture grace by the effect of electrical conductivity of the earth, wherein the sensor module comprises at least two electrodes to measure an electrical resistance and a comparator to activate a digital output when an adjustable threshold is exceeded.

Another embodiment is that the system comprises an analog to digital (ADC) module coupled to the sensor modules, wherein the ADC module comprises an amplifier to adjust amplification from 1 to 128, and a digital filter with a notch provided on an on-chip control register to allow adjustment of the filter cut-off.

Another embodiment is that the system further comprises a leakage detection module configured to detect leakages of alcohol, benzene, CH4, hexane, LPG and CO, due to its high sensitivity and fast response time, and thereby measurements are adjusted by a potentiometer.

Another embodiment is that the system further comprises a turbidity sensor communicatively coupled to the mainframe server to detect water quality by estimating the levels of turbidity, wherein the sensor comprises an LED to transmit a light signal to detect dissolved particles in water by measuring the light transmittance and scattering rate, which changes with the total suspended solids (TSS) in water, wherein when the TTS increases, the liquid turbidity level increases, wherein the sensor comprises an optical transistor to receive reflected light from the water, wherein the turbidity sensor comprises at least two analog and digital signal output modes, when the sensor transmits analog signal the output decreases as the turbidity of water increases, when the sensor transmits digital signal the output signal remains binary as high 1 and low 0, wherein a threshold value of the output is adjusted by a potentiometer; and a processor coupled to the turbidity sensor to measure the voltage signal obtained from the optical transistor and convert

it to a turbidity signal as formula:Turbidity value=-1120.4v2 +5742.3v-4352.9 where v is voltage received from the optical transistor.

Another embodiment is that the system further comprises a pH sensor module wirelessly coupled to the mainframe server through IoT interface module, wherein the pH sensor module is configured to measure a pH scale of water from 0-14, wherein the pH sensor comprises a pH electrodes which contact a certain pH solution and a processor configured to compare a voltage difference from the pH electrodes and convert the voltage difference from the pH electrodes into a pH signal.

To further clarify advantages and features of the present invention, a more particular description of the invention will be rendered by reference to specific embodiments thereof, which is illustrated in the appended drawings. It is appreciated that these drawings depict only typical embodiments of the invention and are therefore not to be considered limiting of its scope. The invention will be described and explained with additional specificity and detail with the accompanying drawings

BRIEF DESCRIPTION OF FIGURES

These and other features, aspects, and advantages of the present invention will become better understood when the following detailed description is read with reference to the accompanying drawings in which like characters represent like parts throughout the drawings, wherein:

Figure 1 illustrates a block diagram of components installed in an automatic monitoring system.

Figure 2 illustrates a system model flow diagram depicting different operations of sensor modules communicating with a main gateway server.

Figure 3 illustrates a smart LoRa-WAN-Zigbee technology system for smart cities, agriculture and underwater monitoring.

Figure 4a-b illustrates a schematic diagram node of a LoRa module.

Figure 5a-b illustrates a schematic diagram node of a Zigbee module.

Figure 6a-b illustrates a schematic diagram of Zigbee-LoRa converter.

Figure 7a-b illustrates a schematic diagram node of underwater monitoring system.

Figure 8 illustrates a LoRa-Wi-Fi gateway module.

Figure 9 illustrates a temperature and humidity sensor module.

Figure 10 illustrates a light intensity sensor module.

Figure 11 illustrates a soil moisture sensor module.

Figure 12 illustrates an analog to digital converter module.

Figure 13 illustrates a leakage detection sensor module.

Figure 14 illustrates a turbidity module sensor.

Figure 15 illustrates a plot depicting a relationship between turbidity and voltage.

Figure 16 illustrates a sensor module for measuring a pH scale of a solution.

Figure 17a-c illustrates a communication module.

Figure 18 illustrates a flow chart of operation of a Zigbee node.

Figure 19 illustrates a flow chart of operation of Zigbee-LoRa converter.

Figure 20 illustrates a flow chart of operation of an agricultural node.

Figure 21 illustrates a flow chart of operation of an underwater node.

Figure 22 illustrates a flow chart of operation of a LoRa gateway.

Figure 23a-c illustrates a user interface module and the parameters of the modules received.

Further, skilled artisans will appreciate that elements in the drawings are illustrated for simplicity and may not have been necessarily been drawn to scale. For example, the flow charts illustrate the method in terms of the most prominent steps involved to help to improve understanding of aspects of the present invention. Furthermore, in terms of the construction of the device, one or more components of the device may have been represented in the drawings by conventional symbols, and the drawings may show only those specific details that are pertinent to understanding the embodiments of the present invention so as not to obscure the drawings with details that will be readily apparent to those of ordinary skill in the art having benefit of the description herein.

DETAILED DESCRIPTION

For the purpose of promoting an understanding of the principles of the invention, reference will now be made to the embodiment illustrated in the drawings and specific language will be used to describe the same. It will nevertheless be understood that no limitation of the scope of the invention is thereby intended, such alterations and further modifications in the illustrated system, and such further applications of the principles of the invention as illustrated therein being contemplated as would normally occur to one skilled in the art to which the invention relates.

It will be understood by those skilled in the art that the foregoing general description and the following detailed description are exemplary and explanatory of the invention and are not intended to be restrictive thereof.

Reference throughout this specification to "an aspect", "another aspect" or similar language means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment of the present invention. Thus, appearances of the phrase "in an embodiment", "in another embodiment" and similar language throughout this specification may, but do not necessarily, all refer to the same embodiment.

The terms "comprises", "comprising", or any other variations thereof, are intended to cover a non-exclusive inclusion, such that a process or method that comprises a list of steps does not include only those steps but may include other steps not expressly listed or inherent to such process or method. Similarly, one or more devices or sub-systems or elements or structures or components proceeded by "comprises...a" does not, without more constraints, preclude the existence of other devices or other sub-systems or other elements or other structures or other components or additional devices or additional sub-systems or additional elements or additional structures or additional components.

Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. The system, methods, and examples provided herein are illustrative only and not intended to be limiting.

Embodiments of the present invention will be described below in detail with reference to the accompanying drawings.

Figure 1 illustrates a block diagram of components installed in an automatic monitoring system. The system of monitoring smart cities, agriculture and underwater is disclosed. The system includes a plurality of sensor modules wirelessly communicating with a mainframe server, wherein the sensor modules are configured to receive a input signal from the mainframe server when the mainframe server is turned ON, wherein the sensor modules are configured to detect a plurality of parameters upon receiving the input signal from the mainframe server and transmit the parameters to the mainframe server. An IoT interface module coupled to the mainframe server at one end and to the sensor modules at the other end, wherein the IoT interface modules are configured to receive input signal from the mainframe server and transmit the received input signal to the sensor modules. A microprocessor control unit communicatively coupled to the mainframe server through the IoT interface module, wherein the microcontroller receivesinput parameters from the different sensor modules, wherein the microcontroller processes the parameters and transmits to the mainframe server.

A cloud interface server is provided in communication with the mainframe server, wherein the cloud interface is configured to receive the parameters, detected by the sensor modules, from the mainframe server and store the parameters in a cloud storage module. A user interface wirelessly communicated to the cloud interface, wherein the user interface transmits an input command to the cloud server, wherein the cloud server upon receiving the input command from the user interface, transmits the stored parameters from the cloud storage module to the user interface.

The first sensor module is configured to detect temperature and humidity with a calibrated digital signal output, wherein the module comprises a resistive-type humidity measurement element and a negative temperature coefficient (NTC) measurement element, wherein the first sensor module is connected to a microcontroller. The microprocessor is coupled to the first sensor module, wherein the microprocessor is configured to transmit an input signal to the sensor module, wherein the microprocessor sets a signal pin as an output pin and controls the signal pin to a low level for a period of at least 18 meters, wherein the sensor module receives commands from the microprocessor in order to measure a value of temperature and humidity, wherein the microprocessor controls the signal pin to a high level, then resets it as an input pin. The microprocessor after a time period of 20-40 seconds, shifts the signal pin to a low level, wherein when the duration time is larger than 40us and the signal pin is not shifted down to the low level, the microprocessor does not communicate with the sensor module. The microprocessor signal pin for a duration of 80 seconds in low level is automatically shifted to a high level and when the signal pin is in the high level the microprocessor communicates with the sensor modules.

The second sensor module configured to detect light, wherein the second module comprises a photodiode to receive an electric current and transmit the electric current to an operational amplifier in order to convert it into a voltage signal, wherein the signal is transmitted to an analog to digital converter to turn it into a 16-bit digital signal, wherein the sensor module measures a wide range (1 - 65535 lx) with adjusted resolution settings of 0.5 lx, Ilx, and 4 lx, wherein the sensor module operates with 3 modes, low resolution mode, first high resolution mode and second high resolution mode.

The third sensor module configured to measure soil moisture grace by the effect of electrical conductivity of the earth, wherein the sensor module comprises at least two electrodes to measure an electrical resistance and a comparator to activate a digital output when an adjustable threshold is exceeded. An analog to digital (ADC) module coupled to the sensor modules, wherein the ADC module comprises an amplifier to adjust amplification from 1 to 128, and a digital filter with a notch provided on an on-chip control register to allow adjustment of the filter cut-off.

A leakage detection module is configured to detect leakages of alcohol, benzene, CH4, hexane, LPG and CO, due to its high sensitivity and fast response time, and thereby measurements are adjusted by a potentiometer.

A turbidity sensor is communicatively coupled to the mainframe server to detect water quality by estimating the levels of turbidity, wherein the sensor comprises an LED to transmit a light signal to detect dissolved particles in water by measuring the light transmittance and scattering rate, which changes with the total suspended solids (TSS) in water, wherein when the TTS increases, the liquid turbidity level increases, wherein the sensor comprises an optical transistor to receive reflected light from the water, wherein the turbidity sensor comprises at least two analog and digital signal output modes, when the sensor transmits analog signal the output decreases as the turbidity of water increases, when the sensor transmits digital signal the output signal remains binary as high 1 and low 0, wherein a threshold value of the output is adjusted by a potentiometer. A processor is coupled to the turbidity sensor to measure the voltage signal obtained from the optical transistor and convert it to a turbidity signal as formula:

Turbidity _value= -1120.4v 2 + 5742.3v-4352.9, where v is voltage received from the optical transistor.

A pH sensor module is wirelessly coupled to the mainframe server through IoT interface module, wherein the pH sensor module is configured to measure a pH scale of water from 0-14, wherein the pH sensor comprises a pH electrodes which contact a certain pH solution and a processor configured to compare a voltage difference from the pH electrodes and convert the voltage difference from the pH electrodes into a pH signal.

Figure 2 illustrates a system model flow diagram depicting different operations of sensor modules communicating with a main gateway server. The method of operation is described as; the Zigbee sensor network consisting of a set of Zigbee sensor nodes, communicating in the 2.4 GHz band, fast data transmission speed, short transmission distance. We perform two Zigbee network clusters to assess the performance of the system. The Lora sensor network: including LoRa sensor nodes, interface in 433 MHz bands, slow data rate, long-distance transmission. The Zigbee-LoRa converter: is the gateway of Zigbee and LoRa networks. The LoRa gateway: Acquire information in the LoRa network and go to the Internet. The Cloud Server: is the server that stores information on the Internet (TTN, ThingSpeak or Blynk).

Figure 3 illustrates a smart LoRa-WAN-Zigbee technology system for smart cities, agriculture and underwater monitoring; Figure 4a-b illustrates a schematic diagram node of a LoRa module; Figure 5a-b illustrates a schematic diagram node of a Zigbee module; Figure 6a-b illustrates a schematic diagram of Zigbee-LoRa converter; Figure 7a-b illustrates a schematic diagram node of underwater monitoring system; and Figure 8 illustrates a LoRa-Wi-Fi gateway module. The system comprises a power supply unit, a machine control unit or microprocessor control unit. The sensors are coupled to the Zigbee gateway and then converted to a required input for a LoRa gateway. Some sensors are directly communicated to the LoRa module.

Figure 9 illustrates a temperature and humidity sensor module. A DHT11 Temperature &

Humidity Sensor features a temperature & humidity sensor system with a calibrated digital signal output. This sensor includes a resistive-type humidity measurement element, and an NTC temperature measurement element. They are connected to a high-performance 8-bit microcontroller, giving superior quality, high-speed response, anti-interference, moreover cost effectiveness. The sensor module detects humidity range: 20% -95%; temperature range: 0-50°C; humidity tolerance of± 5%; and temperature tolerance:± 20C. To be able to communicate with DHT11 in one-wire standard, the microprocessor follows two steps: Send the Start signal to DHT11, then DHT11 confirms it. The MCU sets the Signal pin as Output pin, controls this pin to low level (0) for a period at least 18ms. Then DHT11 will understand the MCU wants to measure the value of temperature and humidity. MCU controls Signal pin to high level (1), then reset it as an Input pin. After about 20-40us, DHT11 will pull Signal pin to low level. If the duration time is larger than 40us but this pin is not pulled down to low level, MCU cannot communicate with DHT11. Signal pin will be low in duration 80us; then, it will be pulled to high level in 80us. By monitoring the Signal pin status, the MCU can tell if it can communicate with DHT11. If the Signal pin is high, then complete the communication process of MCU with DHT11. Once communicating with DHT11, the sensor will send back 5 bytes of temperature and humidity data as follow: Byte 1: integer value of humidity (RH%); Byte 2: the decimal value of humidity (RH%); Byte 3: integer value of temperature (ToC); Byte 4: the decimal value of temperature (ToC); Byte 5: checksum. If Byte 5 = (8 bit) (Byte 1 + Byte 2 + Byte 3 + Byte 4), the value of humidity and temperature are correct; if it is wrong, then the measurement results are not meaningful; and 5 bytes of data will be communicated as bits. If the Signal pin is high level in duration 26-28 us, it is bit 0, and if there exists 70us is bit1.

Figure 10 illustrates a light intensity sensor module. This module interfaces to the BH1750 Light Sensor made by Rohm Semiconductor. The module uses a photodiode with approximately human eye response to sense light. The current signal from the photodiode is converted into a voltage signal by an Operational Amplifier. Then, it goes through the ADC module to turn it into a 16-bit digital signal. Finally, an Ambient Light Data processor stores the light intensity and measurement time in the Data Register (default value 0x0000) and Measurement Time Register (default value 0x45). Therefore, there is no calculation required to measure the LUX value because the sensor directly gives the lux value. The sensor uses the12C communication protocol (SCL, SDA and ADD) to connect with microcontrollers. This module works on a voltage range of 2.4V-3.6V, spends a tiny current of 0.12mA, and can be worked in continuous or single measurement mode. The sensor results do not depend upon the light source used, and the impact of IR radiation is much smaller. This sensor can measure a wide range (1 - 65535 lx) with adjusted resolution settings of 0.5 lx, Ilx, and 4 lx. BH1750 Light Sensor can operate with 3 modes: L-Resolution Mode: resolution is 4 lx, each sample measured in 16 ins, often used in applications requiring a quick response; H-Resolution Mode: resolution is Ilx, each sample measured in 120 ins, usually used for measurement in very dark environments (<10 lx); and H Resolution Mode 2: resolution is 0.5 lx, each sample measured in 120 ins, usually used for light detection application.

Figure 11 illustrates a soil moisture sensor module. The Soil Moisture Sensor measures soil moisture grace to the electrical conductivity of the earth (soil resistance increases with aridity). The electrical resistance is measured between the two electrodes of the sensor. A comparator activates a digital output when an adjustable threshold is exceeded.

Figure 12 illustrates an analog to digital converter module. This is a dual-channel 16-bit analog to digital converter module, easy to connect to a microcontroller via SPI protocol. The module uses a low-noise amplifier that can adjust the amplification from 1 to 128. Sensors can be connected directly via the module, thanks to the input buffer chips. AD7705 is constructed from Delta-Sigma filter with very low noise. Simultaneously, the first notch of this digital filter can be programmed via an on-chip control register, allowing adjustment of the filter cut-off and output update rate.

Figure 13 illustrates a leakage detection sensor module. Module is useful for gas leakage detection (in home and industry). It is suitable for detecting Alcohol, Benzine, CH4, Hexane, LPG, CO. Due to its high sensitivity and fast response time, measurements can be taken as soon as possible. The sensitivity of the sensor can be adjusted by using the potentiometer.

Figure 14 illustrates a turbidity module sensor; and Figure 15 illustrates a plot depicting a relationship between turbidity and voltage. The turbidity sensor detects water quality by estimating the levels of turbidity. It uses light to detect dissolved particles in water by measuring the light transmittance and scattering rate, which changes with the total suspended solids (TSS) in water. As the TTS increases, the liquid turbidity level increases. This sensor provides analog and digital signal output modes. By using D/A Output Signal Switch, we can switch between 2 operating modes: Analog mode: Analog Signal Output, the output signal decreases as the turbidity of water increases; and Digital mode: Digital Signal Output, the output signal can only be high (1) or low (0) and the threshold value is adjusted by potentiometer. This module uses an LED to transmit a light signal, which passes through the water to be observed and is captured by an optical transistor. A processor is connected and measures the voltage signal obtained from the optical transistor and converts it to a turbidity signal as formula; 2 Turbidity _value= -1120.4v +5742.3v-4352.9

Where v is voltage receive from optical transistor.

Turbidity sensors measure water quality in rivers and streams, wastewater and effluent measurements, control instrumentation for settling ponds, sediment transport research, and laboratory measurements.

Figure 16 illustrates a sensor module for measuring a pH scale of a solution. The module includes Module Power: 5.OOV; Module Size: 43 x 32mm(1.69x1.26"); Measuring Range :0 14PH; Measuring Temperature: 0 - 60 °Q Accuracy: ±0.pH (25 °Q; Response Time: < 1min; pH Sensor with BNC Connector; pH2.0 Interface (3 feet patch); Gain Adjustment Potentiometer; and Power Indicator LED.

The pH is a measure of acidosis or alkalinity of a solution; the pH scale varies from 0 to 14. The pH shows the density of hydrogen [H] + ions being in precise solutions. Based on this property, the SEN0161 pH, there is a pH electrode reference. When the measurement electrode contacts with a certain pH solution, the processor compares the voltage difference from those two electrodes and we need convert it into a pH signal. When using this sensor, stable power and standard 5V DC will produce more accurate results. Besides, regularly clean the measurement electrode with demonized water and periodically calibrate the scale. The calibration steps are as follows: Step 1: The calibration takes place in an environment of 25 °C is best. Prepare three reliable and known standard pH solutions. If the sample to be measured is acidic, the sample should have a pH of 4.00, and the example to measure is alkaline, the sample should have a pH of 9.18. Besides, a distilled water solution with a pH of 7.00 should be prepared. Step 2: Connect the module to the Arduino and observe the information obtained via Serial. Place the pH probe into distilled water. The pH value obtained on the Serial will be compared with 7.00 to find Offset value; and step 3: Using the Offset value, put the pH probe into the sample solution with a pH of 4.00. Please wait for the results to stabilize after 1 minute and use the Adjustment potentiometer to correct it to 4.00. Do the same for pH 9.18 sample solution. This has completed the calibration and can proceed using the pH sensor.

Figure 17a-c illustrates a communication module. The Zigbee Module adopts CC2530 IC as the Transmitting and Receiving chip, a System-On-Chip solution for 2.4Ghz IEEE 802.15.4 and Zigbee Application. The CC2530 has multiple operating modes, making it deeply adapted for systems where ultralow power consumption is required. Short transition times between operating modes further ensure low energy consumption. Use the default Configuration Button, the module is configured through 4 main steps: Step 1: Select the baud rate declared in the Arduino code for the module to communicate. With no power supply, press and hold the button, then power on. Four configuration indicator LEDs on the module will flash, indicating access to the Configuration mode. Release the button, then press the sequential button to select the appropriate baud rate level according to the picture below.

2400 4800 M9600 14400 19200* 38400 *57600 115200

Step 2: Select the channel. Press and hold the button to save the settings; you will see four LEDs with the blinking signal to switch to the next configuration mode: Chanel setting mode. Sixteen channels can be selected according to the status of four indicators leds, note that the modules that you want to receive together must have the same channel (not necessarily the same baud rate because baud rate is only used to communicate with the microcontroller). Step 3: Select the Transmission mode. After choosing Chanel, press the button to go to next step, four LEDs on the module will blink to indicate access to Transmission configuration mode. Release the button, then press the sequential button to select the transmission mode. The Zigbee CC2530 module has two transmission modes: Point to Point: Used to transmit between two modules to each other. LED configuration for two modules as shown

Broadcast: Users can create a transmission network between nodes to create their own network. All modules need to be configured with Chanel and Broadcast the same, when one module transmits, all the remaining modules will receive, and the function of the modules is equivalent.

-Point to point A end -Point to point B end Configuration as follows

Boardcast

Step 4: Confirm to save and complete the setting. After successful installation, all data will be saved forever, even during a power failure, meaning we only need to do this once.

The Lora SX1278 433MHz module uses the LoRa standard SX1278 interface chip with two critical factors: energy-saving and the ultimate long-range wireless solution, in addition to being configurable to create the network, is currently developed and used a lot in IoT research. Lora SX1278 module is capable of the transceiver with a distance of10km. SX1278 uses LoRa Spread Spectrum modulation technology while supporting multiple modulated modes such as FSK, GFSK, MSK, GMSK, LoRa TM, and OOK. RF transceiver power: + 20dBm-100mW with high sensitivity: -148dBm. SX1278 provides a half-duplex SPI interface with a microcontroller. SX1278 possesses many outstanding features compared to other LoRa modules such as communication speed up to 300 kbps, dynamic range 127dB RSSI, and packaging technology CRC up to 256 bytes. The Wi-Fi LoRa 32 is a perfect IoT dev-board. This is a multi-function module that integrates many standard communication technologies today, such as LoRa, Wi-Fi, and BLE. Besides, the module has a built-in Li-Po PIN power management module and a 0.96 inch 128*64 dot matrix OLED screen. Wi-Fi LoRa 32 uses dual-core 32-bit MCU and Ultra Low Power core ESP32 and LoRa node chip SX1276/SX1278 that perfect for the LoRaWAN protocol. The ESP32 chip has a high level of low-power performance, including top resolution clock gate control, power-saving mode, and dynamic voltage management. This chip is produced for mobile devices, wearable electronics, and the Internet of things applications with resting current 800uA ±50uA. Based on the LoRaWAN source code, Wi-Fi LoRa 32 is made with many improvements to the low-power part of the code. Within one transmission cycle of the system, only a few milliseconds were working, and the rest of the time was in the deep sleep state.

Figure 18 illustrates a flow chart of operation of a Zigbee node. Zigbee node is responsible for collecting LPG and CH4 concentration data in the air. In this model, two Zigbee Clusters are configured for Broadcast communication, so the Zigbee nodes have similar functions. We proposed the Token Flag, worked as a communication status flag. When Token Flag free (0), one Zigbee node can catch and turn it into busy status (1). After informed to other nodes to the message, "Pipe is Busy." and required them to wait, this node can communicate with the Zigbee LoRa Converter Module. When the communication completed, this Zigbee node informs the other nodes of the message, "Pipe is Free." and set Token Flag to zero. And so forth, all the nodes will transmit sensor information to the Converter. In order to get the most accurate LPG and CH4 signals, we designed the hardware using a 16-bit high-resolution Delta-Sigma ADC unit and equipped with a 50/60 Hz noise filter. At the same time, a digital filter was developed to average the measurements to eliminate hardware errors.

Figure 19 illustrates a flow chart of operation of Zigbee-LoRa converter. Zigbee-LoRa Converter converts the entire Zigbee signal in a Cluster that it manages into a LoRa signal and passes it to the LoRa gateway. This Converter always listens to the Zigbee link, and if a Zigbee node captures the Token flag, it establishes a link with that node and receives information from the sensor. The communication ended, and the Token flag was released. After the information has been collected in the entire Cluster, the Converter will wait for signals from the LoRa gateway. If the command from the LoRa gateway has an identical ID, it will convert the collected data into LoRa form and pass it to the gateway.

Figure 20 illustrates a flow chart of operation of an agricultural node. The agriculture LoRa node collects environmental parameters such as temperature, humidity, light intensity, and soil moisture then sends these signals to the LoRa gateway. The three types of sensors used in this node are: DHT11 communicates with the 1-wire protocol. Soil moisture sensor communicates with ADC. We use a digital filter that averages the ten measurement samples applied for more accurate measurements. BH1750 communicates with the 12C protocol. In this paper, we use continuous measurement mode with a sample taken every 120 seconds. Similarly, we use a digital filter that averages five measurement samples for more accurate measurements.

Figure 21 illustrates a flow chart of operation of an underwater node. Underwater LoRa node collects underwater environmental parameters such as pH, and turbidity then sends these signals to the LoRa gateway. The two types of sensors used in this node are:

D Turbidity sensor SEN0189 communicates with the ADC. We proposed using recursive filters to increase the accuracy of the measurement. A recursive filter calculates a new, smoothed value (yn) by using the last smoothed value (yn - 1) and a new measurement (xn): yn = w x xn

+ (1 - w) x yn - 1. The volume of smoothing is controlled by a weighting parameter (w). The weight is a value between 0% and 100%. When the weight is large (say 90%), the filter does not smooth the measurements very much but responds immediately to changes. If the weight is low (say 10%), the filter smooths the measurements significantly but does not respond quickly to changes. This filter does not need much memory (just enough to store the last measurement) and we can control how much filtering is applied with a single parameter (the weight). It also works well in battery-powered applications such as underwater environment because we do not need to make many measurements at once. The pH sensor SEN0161 communicates with the ADC. We proposed a 2-step measurement procedure: As a first step, the system takes ten measurements and arranges them in order from big to small. In the second step, the system takes an average of 6 samples from sample 3 to sample 8 (remove the two most significant samples, i.e., sample 1 and sample 2, and two smallest samples, i.e., sample 9 and sample 10) to more accurate measurements. The formula for converting the voltage value to the pH value is deduced from the experiment.

Figure 22 illustrates a flow chart of operation of a LoRa gateway. The LoRa gateway is responsible for collecting all data of the system and sending it to 2 Cloud servers: ThingSpeak and Blynk. The gateway uses a polling mechanism to request LoRa devices to send data back. This data will be converted into a format following the MQTT protocol of ThingSpeak and Blynk's Virtual Pin format for updating to the server.

Figure 23a-c illustrates a user interface module and the parameters of the modules received in a time graph. The mail function is such that a notification is generated and an email function allows the system to send collected information to any E-mail. A Twitter function allows the system to post tweets describing status 1 time per five seconds. A Push Notification function allows setting of alerts on Smartphone. The text is displayed on the user interface. And the system allows to display system parameters in numerical format. A Graph is also displayed and allows to display system parameters as real-time graphs.

Some advantages of the present system are as follows; the system can be deployed on a large scale easily thanks to the LoRa connection. The system is compatible with existing Zigbee systems. The system can communicate with a variety of sensors and is very flexible in installation. Optimized algorithm helps the packet loss rate lower than 0.5%. The software monitoring parameters are intuitive and easy to use on the web interface and smartphone interface. The present invention is applied to Smart City Monitoring; Industrial Application Monitoring; Agriculture Monitoring and Underwater Monitoring.

The drawings and the forgoing description give examples of embodiments. Those skilled in the art will appreciate that one or more of the described elements may well be combined into a single functional element. Alternatively, certain elements may be split into multiple functional elements. Elements from one embodiment may be added to another embodiment. For example, orders of processes described herein may be changed and are not limited to the manner described herein. Moreover, the actions of any flow diagram need not be implemented in the order shown; nor do all of the acts necessarily need to be performed. Also, those acts that are not dependent on other acts may be performed in parallel with the other acts. The scope of embodiments is by no means limited by these specific examples. Numerous variations, whether explicitly given in the specification or not, such as differences in structure, dimension, and use of material, are possible. The scope of embodiments is at least as broad as given by the following claims.

Benefits, other advantages, and solutions to problems have been described above with regard to specific embodiments. However, the benefits, advantages, solutions to problems, and any component(s) that may cause any benefit, advantage, or solution to occur or become more pronounced are not to be construed as a critical, required, or essential feature or component of any or all the claims.

Claims

WE CLAIM

1. A system of monitoring smart cities comprising

a plurality of sensor modules wirelessly communicating with a mainframe server, wherein the sensor modules are configured to receive a input signal from the mainframe server when the mainframe servers turned ON, wherein the sensor modules are configured to detect a plurality of parameters upon receiving the input signal from the mainframe server and transmit the parameters to the mainframe server;

an loT interface module coupled to the mainframe server at one end and to the sensor modules at the other end, wherein the loT interface modules are configured to receive input signal from the mainframe server and transmit the received input signal to the sensor modules;

a microprocessor control unit communicatively coupled to the mainframe server through the loT interface module, wherein the microcontroller receives input parameters from the different sensor modules, wherein the microcontroller processes the parameters and transmits to the mainframe server;

a cloud interface server in communication with the mainframe server, wherein the cloud interface is configured to receive the parameters, detected by the sensor modules, from the mainframe server and store the parameters in a cloud storage module;

a user interface wirelessly communicated to the cloud interface, wherein the user interface transmits an input command to the cloud server, wherein the cloud server upon receiving the input command from the user interface, transmits the stored parameters from the cloud storage module to the user interface.

2. The system as claimed in claim 1, wherein the system comprises

a first sensor module configured to detect temperature and humidity with a calibrated digital signal output, wherein the module comprises a resistive-type humidity measurement element and a negative temperature coefficient (NTC) measurement element;

a microprocessor coupled to the first sensor module, wherein the microprocessor is configured to transmit an input signal to the sensor module, wherein the microprocessor sets a signal pin as an output pin and controls the signal pin to a low level for a period of at least 18 meters, wherein the sensor module receives commands from the microprocessor in order to measure a value of temperature and humidity, wherein the microprocessor controls the signal pin to a high level, then resets it as an input pin;

the microprocessor after a time period of 20-40 seconds, shifts the signal pin to a low level, wherein when the duration time is larger than 40us and the signal pin is not shifted down to the low level, the microprocessor does not communicate with the sensor module; and

the microprocessor signal pin for a duration of 80 seconds in low level is automatically shifted to a high level and when the signal pin is in the high level the microprocessor communicates with the sensor modules.

3. The system as claimed in claim 1, wherein the system comprises a second sensor module configured to detect light, wherein the second module comprises a photodiode to receive an electric current and transmit the electric current to an operational amplifier in order to convert it into a voltage signal, wherein the signal is transmitted to an analog to digital converter to turn it into a 16-bit digital signal, wherein the sensor module measures a wide range (1 - 65535 lx) with adjusted resolution settings of 0.5 lx, Ilx, and 4 lx, wherein the sensor module operates with 3 modes, low resolution mode, first high resolution mode and second high resolution mode; a third sensor module configured to measure soil moisture grace by the effect of electrical conductivity of the earth, wherein the sensor module comprises at least two electrodes to measure an electrical resistance and a comparator to activate a digital output when an adjustable threshold is exceeded; and an analog to digital (ADC) module coupled to the sensor modules, wherein the ADC module comprises an amplifier to adjust amplification from 1 to 128, and a digital filter with a notch provided on an on-chip control register to allow adjustment of the filter cut-off.

4. The system as claimed in claim 1, wherein the system further comprises

a leakage detection module configured to detect leakages of alcohol, benzene, CH4, hexane, LPG and CO, due to its high sensitivity and fast response time, and thereby measurements are adjusted by a potentiometer;

a turbidity sensor communicatively coupled to the mainframe server to detect water quality by estimating the levels of turbidity, wherein the sensor comprises an LED to transmit a light signal to detect dissolved particles in water by measuring the light transmittance and scattering rate, which changes with the total suspended solids (TSS) in water, wherein when the TTS increases, the liquid turbidity level increases, wherein the sensor comprises an optical transistor to receive reflected light from the water, wherein the turbidity sensor comprises at least two analog and digital signal output modes, when the sensor transmits analog signal the output decreases as the turbidity of water increases, when the sensor transmits digital signal the output signal remains binary as high 1 and low 0, wherein a threshold value of the output is adjusted by a potentiometer; and

a processor coupled to the turbidity sensor to measure the voltage signal obtained from the optical transistor and convert it to a turbidity signal as formula:

Turbidity _value = -1120.4v 2 +5742.3v - 4352.9, where v is voltage received from the optical transistor.

5. The system as claimed in claim 1, wherein the system further comprises

a pH sensor module wirelessly coupled to the mainframe server through IoT interface module, wherein the pH sensor module is configured to measure a pH scale of water from 0-14, wherein the pH sensor comprises a pH electrodes which contact a certain pH solution and a processor configured to compare a voltage difference from the pH electrodes and convert the voltage difference from the pH electrodes into a pH signal.

MAINFRAME SERVER CLOUD MICROPROCESSOR INTERFACE CONTROL UNIT 2020102711

IoT SENSOR INTERFACE MODULES MODULE

USER INTERFACE

FIG. 1

FIG. 2

FIG. 3

FIG. 4a

FIG. 4b

FIG. 5a FIG. 5b

FIG. 6a FIG. 6b

FIG. 7a FIG. 7b

FIG. 8 FIG. 9

FIG. 10

FIG. 11 FIG. 12

FIG. 13

FIG. 14 FIG. 16

FIG. 15

FIG. 17a FIG. 17b

FIG. 17c

FIG. 18

FIG. 20 FIG. 19

FIG. 22 FIG. 21

FIG. 23a

FIG. 23b

FIG. 23c