In this page there 12 categories of Raspberry Pi projects with more projects with abstracts and demo video. Click the category to view plenty of project in that specific category.
Categories of Raspberry Pi projects
- Raspberry Pi projects for Beginners with codes
- IoT Based Raspberry Pi projects
- OpenCV based Raspberry Pi projects
- Robotics projects using Raspberry Pi
- Electrical Projects using Raspberry Pi for EEE
- Brain Computer Interface (BCI) projects using Raspberry Pi
- Deep learning & Machine Learning projects using Raspberry Pi
- Natural Language Processing (NLP) with Raspberry Pi
- ROS with Raspberry Pi
- Raspberry Pi with Lidar
- Raspberry Pi with Matlab Hardware projects
- Artificial Intelligence using Raspberry Pi
Mapping, Path Planning & Path Following Robot using ROS, LIDAR with Raspberry PiClick here for Video Demo
This is one of the Low-cost ROS bot, which has simple structure uses ROS (Robotic Operating System) software library of version ROS Kinetic booted with Raspberry Pi and also interfaced with RPLidar in the front top portion of the Bot. This low-cost turtle bot emerges with features like SLAM (Simultaneous Localization and Mapping), Path planning and Path Following. which has the capability to reach the destination automatically after its destination is fixed in the Map. For those Applications, we are using Matlab’s Robotic Operating System Software package to communicate with ROS in the Raspberry Pi using ROS Network Configurations.
SLAM Robot using ROS & LIDAR with Raspberry piClick here for Video Demo
This low-cost mapping bot emerges with features like SLAM (Simultaneous Localization and Mapping). which has the capability to form the Map of the environment using Lidar scans using Matlab’s Robotic Operating System Software package to communicate with ROS in the Raspberry Pi using ROS Network Configurations.
Obstacle avoidance ROS RobotClick here for Video Demo
In this proposed system, by using 360-degree lidar is used to map the environment with an obstacle. And by using path planning algorithm robot chooses its own path to reach some destination point by avoiding the obstacle.
Raspberry Pi based voice assistance using Android appClick here for Video Demo
A virtual assistant is a well-known application, which includes all functionalities like cloud, IoT and some assisting actions. This project helps you to begin with virtual assistance using android mobile which is interfaced with the Raspberry Pi. Android mobile is used only for mic interface so that you can give the voice commands through the Android mobile to the raspberry pi via Bluetooth.
Path Following Robotic Car using ROS,Lidar with Raspberry piClick here for Video Demo
In this project Raspberry Pi is used which the RPlidar is interface. The operating system used is ROS booted in 16GB SD card. This system also contains Arduino UNO to control the robotic car which has Bluetooth module interfaced with it. Simultaneous localisation and mapping is done in Matlab by receiving Laser scan data from the ROS. Path planning is done by choosing the destination point in the map obtained in the Matlab. Based on the coordinates Matlab sends command to Arduino via Bluetooth to control the car.
Raspberry pi projects using Camera
The main aspect of this gesture based device is the capturing of hand movements by the camera which interprets and processes the acquired information, the processing of this information, in the form of images is done with the help of open CV and raspberry pi.
This project includes the development of an image-based vehicle classification system as an effort to seek for a robust vision-based vehicle classification system.
Traffic Sign Recognition (TSR) systems employ vehicle mounted cameras that identify traffic signs while driving on the road. Typically, these systems recognize speed limit signs, stop signs and warning signs such as pedestrian crossing, railroad crossing etc. Their primary function is to inform the driver of recent traffic signs that may have been missed due to distraction or inattentiveness. A camera scans the roadside for signs. Real-time image processing software identifies, interprets and displays them on a panel on the vehicle dashboard. TSR systems perform the following basic functions.
Electronic voting machine has already been developed and widely used in many developed countries. But most of them use Radio Frequency ID. In developing countries RFID for each person does not exist. And using RFID is still a costly solution. Some of the developing countries use image processing technique to detect citizens. But only image processing is not enough. Keeping these problems in mind we have developed this project where raspberry pi will be used as host.
A couple of books projects for you today. One is simple, practical and of great use to the visually-impaired. The other is over-complicated, and a little bit nuts; nonetheless, we think it’s rather wonderful; and actually kind of useful if you’ve got a lot of patience. We making open-source audiobook software so you can build a reader with very simple raspberry pi controls. Here we present to you the Brick Pi Book reader which can read aloud a real book and also turn the pages of the book
Fruit counting is an important task for growers to estimate yield and manage orchards. An accurate automated fruit detection and counting algorithm gives agricultural enterprises the ability to optimize and streamline their harvest process. Through a better understanding of the variability of yield across their farmlands, growers can make more informed and cost-effective decisions for labor allotment, storage, packaging, and transportation. Estimation of fruit count from images is a challenging task for a number of reasons including appearance variability due to illumination, and occlusion due to surrounding foliage and fruits.Fruit counting algorithms relied onOpen computer vision methods involving hand-crafted features that exploited the shape, color, texture or spatial orientation of various fruit. A counting algorithm based on a second convolutional network then estimates the number of fruit in each region. Finally, color maps that fruit count estimate to a final fruit count.
Portable Camera Based Text and Product Label Reading From Hand-Held Objects for physically challenged Persons
In the project, the system provides a fully automated tracking and monitoring of the vehicle which helpful for school bus, their owners Children’s safety and also it provides the accurate arrival time of the vehicle at particular location or stop.The proposed system get tracking information of the vehicle like vehicle number (Unique ID), location, speed, Date, Time and store into the database of Raspberry.The system also provides students safety mechanism with the help of temperature sensor and gas leakage sensor.The proposed system provides more safety and securesolution using android application for wrong path alert.
Gesture Recognition is a technology which is used to identify human physical gestures with the help of some algorithms. Gesture recognition recognizes the hand, tracks the hand movements & also provides information about hand position orientation. In this system finger tip is made to be the pen for art. For that color markers should be placed at the tip of the finger, according to the color movement art can be performed. By using camera we have to draw in front of that camera in the air so that color has been processed and make an art in white frame. Color can be configured using HSV (Hue Saturation Value).
In our day to day life, we are watching more objects, places and things. Some things we are not able to identify what are those, usually if we want to know about that object we have to define the structure of an object in internet to identify the object. Suppose if we are having a project on a certain thing which we haven’t seen before, it is difficult to search about it. So this Cam_find is used to capture the image of any object and search in websites and narrates the user about that object automatically. For ex: Image like statues, it will check for that statue in internet and identify the statue then narrates about that statue automatically.
Assistive technologies are being developed for deaf and dump people in order to live confidently. This project work proposes a camera-based assistive gesture reading framework to help blind persons to read text labels. Here we are using 16 sign detection, Functions of each sign can be easily configurable to certain process (ex: For any voice command, asking for some needs or typing any letters, etc.,) using the hand sign which is detected using a camera and sign detection is done using OpenCV.
The solution we provide for Traffic management by having a special intelligence which the images of road feed from the cameras (webcam or IP camera) at traffic junctions for real time traffic density calculation using image processing. It also focuses on the algorithm for switching the traffic lights according to vehicle density on the road, thereby aiming at reducing the traffic congestion on roads which will help lower the number of accidents. In turn, it will provide safe transit for people and reduce fuel consumption and waiting time. It will also provide significant data which will help in future road planning and analysis. In further stages multiple traffic lights can be synchronized with each other with an aim of even less traffic congestion and free flow of traffic. The vehicles are detected by the system through images instead of using electronic sensors embedded in the pavement. A camera will be placed alongside the traffic light. It will capture images sequences. Image processing is a better technique to control the state change of the traffic light. It shows that it can decrease the traffic congestion and avoids the time being wasted by a green light on an empty road. It is also more reliable in estimating vehicle presence because it uses actual traffic images.
From this project you will learn to use computer vision for detecting eyeball and tracking eyeball movement for cursor control.
This project teach you to about how to control the hardware using eyeball movement using OpenCV on Raspberry Pi
Robotics plays a major role in lot of Automation Fields. Robotic Actions become more efficient in upcoming years. Starting from gesture, line follower and Path follower several Path estimation algorithms are developed for robotic movement. Line follower user IR sensor to travel along the line. The main aim of the Paper to Propose a system that has one robot which is used for Defense and Surveillance Application that work is to give live streaming about that place Controlling Action happens in webpage Provided by the Raspberry Pi’s Server. Live streaming can be happening through Local host connected to the Raspberry which Provides a local Server to control the raspberry pi. It Provides Low cost robot which performs all the surveillance operation with live Streaming.
Reception is there to check the Visitors details and Employee details and all other details of the company. That all are managed by one person he is called Receptionist. In this Project, we are developing one system that Performs the work of Receptionist in an automatic manner. Here we use Face recognition to find out the Person visited the company. Open CV Algorithm is used to extract the facial features of humans. If the new person visited the company means his face is Stored in Database. If the other old persons visited the company means This system book the Appointment for that person. Once the face is Recorded means it can identify whenever the Person visited the company. The System reduces the human work and manpower. This system is Portable and Available at low cost.
Computer Vision and Internet of thing (IOT) is the emerging technologies now a days. To reduce the man power for security aspects in this project a Face Tracking system has been implemented using a single board computer i.e. Raspberry Pi 3 which will act as the CPU in which we will do the coding part using Python and a module named Open Source Computer Vision (OpenCV). A USB camera is attached to the raspberry pi which will be used for face tracking whenever the person come before the camera it will track the face of the person, the main advantage of this is it can track multiple faces at the same time in the single frame. This system make our work easier to track a face where we don’t have to manually track that. OpenCV with python make this system more accurate and easy to track any face. When a person face is tracked in the camera it will give the alert to maintain security especially in the areas where persons are not allowed. The alert is given using the Twilio API which will automatically send the message to the owner when even a face is tracked and detected.
Digital Art Drawing In the Air Through Camera using Raspberry Pi which uses skin colour , HSV
Drunk driving is the reason behind most of the deaths, so the Drunk Driving Detection with Car Ignition Locking Using Raspberry Pi aims to change that with automated, transparent, noninvasive alcohol safety check in vehicles. The system uses raspberry pi with alcohol sensors, dc motor, and LCD display circuit to achieve this purpose. System uses alcohol sensor with, raspberry pi with dc motor to demonstrate as vehicle engine. System constantly monitors the sensitivity of alcohol sensor for drunk driver detection. If driver is drunk, the processor instantly stops the system ignition by stopping the motor. If alcohol sensor is not giving high alcohol intensity signals, system lets engine run. The raspberry pi processor constantly processes the alcohol sensor data to check drunk driving and operates a lock on the vehicle engine accordingly. At the same time it is connected to a network from where the person who is driving id being monitored and if any necessity of help will be provided to him by the caretaker who will get the alert on the monitoring webpage automatically.
This paper we propose a security patrolling robot that uses night vision camera for securing any premises. The robotic vehicle moves at particular intervals and is equipped with night vision camera and sound sensors. It uses a predefined line to follow its path while patrolling. It stops at particular points and moves to next points if sound is detected. The system uses IR based path following system for patrolling assigned area. It monitors each area to detect any intrusion using 360degree rotating HD camera. It has the ability to monitor sound in the premises. Any sound after company is closed and it starts moving towards the sound on its predefined path. It then scans the area using its camera to detect any human faces detected. It captures and starts transmitting the images of the situation immediately on sound or human face detection. Here we use IOT Local Area Network (LAN) for receiving transmitted images and displaying them to user with alert sounds. Thus we put forward a fully autonomous security robot that operates tirelessly and patrols large areas on its own to secure the facility
In any driving scenario, lane lines are an essential component of indicating traffic flow and where a vehicle should drive. It’s also a good starting point when developing a self-driving car! In this project, we will be showing you how to build your own lane detection system in OpenCV using Python. Here’s we will be using a particular structure for this pipeline. In this paper Raspberry pi is used in which OpenCV wrapper is used with python programming language where a simulation is implemented for the curved lane detection is done by using Color Filtering in HLS with Canny Edge Detection and Hough Line Detection which will be applied to the video to detect the curved lane. It’s an effective way which can used for self-driving and make the driving automation. OpenCV plays an important role in this and the lane detector can be applied to both images and the videos also.
Automatic vehicle license plate recognition is an important component of modern intelligent transportation systems (ITS). Generally vehicle license plate recognition is divided into several steps including license plate extraction, image region which contains a license plate, character segmentation, and character recognition. Automatic license plate recognition system using Camera mounted over the exposure system image of the license plate is captured and the image is processed to extract the license number. The extracted information can be used with or without a database in many applications, such as electronic payment systems toll payment, parking fee payment, and freeway and arterial monitoring systems for traffic surveillance. If a vehicle tries to cross traffic rules, its license number is extracted and information regarding the offense along with the license plate no is sent to the Traffic Control Section for further legal actions to be taken. An alarm is raised to inform the on field policeman about the offense. It should also be generalized to process license plates from different nations, provinces, or states.
Monitoring of homes has seen a growing need in emerging times. By means of this paper, we put forward a Webcam robot which can be integrated into any kind of household. The base controller of the robot will be the powerful Raspberry Pi 3 Model B. A webcam attached to the Pi monitors the area and sends a notification when any trespassing or obtrusion is detected. The camera also possesses face recognition algorithm which will possess the ability to identify the person responsible for the motion triggering. If it is an authorized personnel, the on board voice assistant will start talking with the person. The notification will be sent only when it’s an unauthorized personnel and will contain pictures clicked of the trespasser and also activate live streaming of the webcam feed. The live streaming ability of the Pi allows the camera feed to be analyzed from any location using internet. With such a system, every user will feel more sheltered while they’re not at their place of residence or when they’ve left their children and old ones alone at home.
Raspberry Pi has mostly used hardware to interface/working with the camera-based application. Mainly for Open CV (Open Computer Vision) based applications. As the Raspberry Pi beginner, without USB camera, we can also use our mobile camera to capture an image to process in Raspberry Pi using IP cam. So that USB camera is not needed, with also high resolution. But frame processing will be a little bit slow when compared to USB camera. The mobile which we gonna uses the camera should be connected with the same network at which the Raspberry Pi is connected so that it acts as Local IP to work on IP camera.
Raspberry Pi has mostly used hardware to interface/working with the camera-based application. Mainly for Open CV (Open Computer Vision) based applications. As the Raspberry Pi beginner first to learn about to capture the image using Raspberry Pi with a USB camera. If the image is captured using below code, the captured image is stored in the current directory.
Raspberry Pi can be changed into automatic selfie-booth which is installed in some other countries, as by having little idea by using Raspberry Pi fun ideas about by making it as Selfie booth using Open CV technology. This Raspberry Pi project features the facilities like the automatic and manual selfie-booth system, the image can be captured using buttons as well as by Open CV technology it detects the face first and classifies each part of our face to detect mouth and after detecting the smile in the face it captures the image.
In most place security surveillance camera is turned off because of the insufficient storage, It causes more trouble when some disaster occurs. To prevent from storage problems we are developing this Raspberry Pi project with a camera which takes video with time-lapse technology for storage optimization, based on our storage video features are optimizable.
Wildlife photography is very much difficult to work to stay on the location more than a while to find the animals and to capture the image at the close. This is a simple Raspberry Pi beginner project which we implemented this with the camera, already miniature camera is placed in the forest to capture the unnoticed action of livings. But by interfacing this technology with the camera, Images can be captured only if any motion is detected. Raspberry Pi which takes video with motion-based technology for storage optimization, with action based camera to capture the image.
Image processing is most needed technology for every type of applications like to process the image and to do some physical activities based on the results. Likewise in Python programming which also used for many machine learning projects, The technology which plays a major role in image processing using python programming is Open Computer Vision(Open CV). By using this Raspberry Pi with Open CV project, you will learn to use Open CV on Raspberry Pi to detecting the Facial expression. This is done by placing 68 landmarks in the face and to analyze those dots to predict the expression.
Open CV is the technology used to do image processing using Python Programming, which here is used to detect the Facial parts using 68 landmark predictor. This is implemented in Raspberry Pi system which is connected with the camera can be used to implement some hardware applications like detecting faces in the group the technology used in a mobile camera to set the focus for every faces, same which implemented using Raspberry Pi Open CV. This can be further modified based on the applications like counting the number of people in the group.
The probability of Accident happening by the Driver is higher when compared to other probabilities, especially driving at night, because of many parameters like drowsiness and by alcohol consumption. So if the possibility of drowsiness is identified, then the accidents can be avoided. So we are implementing this project to monitor the driver by noticing the parameter of drowsiness detection using open CV technology and monitoring alcohol consumption.
The concept like an Autonomous car which is emerged with more sensor to make it as autonomous, for detecting obstacles, vehicles or pedestrians. Which are all done by sensor fusion which is done by merging every sensor reading to predict the pedestrians, Instead of using a lot of sensors to predict the obstacle, we can use the camera to identify the distance between the camera to the object, which is used to reduce the number of the sensor being used to predict the obstacle.
There is two technique to detect an object, Static and Dynamic from which tracking the object when it is moving. The system is kept constant as static, it will capture the video and by using the computer vision technology, the system will track the moving object. The system at existing, which will track the object based on color, but this system, enables the camera to track the moving object using Open CV.
A surveillance camera is fixed in many places of our surrounding. However, in every surveillance system, it only records the video and gets stored in the Storage drives. To make the surveillance camera to the next level, we are using Open CV technology to stream the video. If it detects the human in the camera, few seconds of video have been captured and sent to the admin via SMTP protocol.
Endoscopy is the camera-based technology used to view the internal body by inserting the Endoscopy camera into the body. This is water resistant miniature camera, which can be easily inserted into the body to view the internal organs without operating body. This medical facility is integrated with the Raspberry Pi so that we can view the video of our internal organ remotely and also it is helpful to analyze the video or to do any IoT technology to process the video by viewing the video in a webpage using localhost.
IoT Using Raspberry PI
In this paper we going to make robot for monitoring the family activities and also to monitor the health of our family. In view of the present family security coefficient and poor family environment information control were complicated, family members can’t access to environmental information conveniently, this paper proposed a ARM cortex series nuclear core processor used in the Internet of things of the family embedded robotic system, by used the 802.11 g and TCP/IP, HTTP to realize the infinite distance signal transmission, and adopted the H264 video coding scheme for real-time monitoring of video image signal coded, and decoded RTP/RTCP for video streaming transmission, and used C/S architecture, B/S architecture, the designer of the database with the server to ensure that the family monitoring data stored and displayed in real time, and used SSH protocol to ensure that the remote control and the safety reliability of the robot. By the experimental results, the feasibility of the scheme was verified, which had a good effect of monitoring.
Now a day’s due to global warming and climate changes there are challenging situations in coal mine. To reduce the cost as well as to improve the productivity along with product quality the automation in the field of coal mine is necessary, which will also reduce the mine workers efforts. This project proposes a design of a IOT system with MQTT protocol, by the help of Raspberry pi controller which is able to monitor the temperature, humidity, gas and status of smoke in an under ground mine. This system utilizes low power, cost effective Raspberry pi, a temperature sensor LM35, humidity sensor SYSH220, smoke detector, gas sensor for sensing the mine climate parameters and Wi-Fi for remote logging of data at central location to control the climate state. Every sensor values gets reported through MQTT protocol at every certain interval of time. If there is any sudden increase in any of those sensor values along with data log, ten seconds of video has been captured and sends to the server’s mail.
Security has always been an important issue in the home or office. A remote home security system offers many more benefits apart from keeping home owners, and their property, safe from intruders. The system is composed of the Doorbell interfaced with Raspberry pi, whoever press the doorbell, the camera gets triggered and capture their face and it checking for their face with its database which already has registered faces, if it is an authorized person door will open, otherwise it sends an OTP with their photograph of the intruder to server mail. Only when non authorized person entered that OTP, that face gets added to the authorized person’s database to open the door.
This paper presents the development of a smart sensor based environment monitoring system, in remote villages especially for crop fields. Basically, it is difficult to monitor the environment, weather all the time, so we proposed this project Crop field, to monitor the weather and any environment changes using IoT through SMTP and MQTT which having some sensors like Temperature sensor, Moisture sensor, Gas sensor and LDR which measures respective parameters throughout the day. At the same time sensors are not having ability to predict the weather accurately, so we are using weather cloud to know the current weather and climate change yet to happen, like every weather information is monitored, when there are any chances of rain in weather cloud then the camera gets triggered and capture the image of the atmosphere with the data log of current weather logs and upcoming weather logs are sent to mail by the user. And also parameters measured by sensors are sent through MQTT protocol, which having the common node, when ever MQTT client comes into the network, not only the current data log, but also the old data also sent to that MQTT client which has high speed transmission.
Home automation is becoming more and more popular day by day due to its numerous advantages. This can be achieved by local networking or by remote control. This paper aims at designing a basic home automation application on Raspberry Pi through detecting the person’s presence by detecting the presence of an NFC band within its range. LEDs were used to indicate the switching action.The user who is having the NFC wrist band, which their device is pre-configured with this system, so that it always searching for the device, when the NFC wrist band comes into the range, Light and Fan will be turned ON automatically, similarly when the band is in out of range all appliances should turn OFF.
This Project Proposes a system, that system performs water quality monitoring and Regulated water supply operation. We have some more sensor like pH, conductivity sensor, Flow sensor, Temperature Sensor and LDR module. By using this sensor value, we calculate the continually and taking the data, analyze after any problem in the sensor value we will calculate to the water purity and sent the alert message to the authorized person by using the IOT Technologies. We have the purity sensor and pH sensor by using this we got the sensor values, at last, we get the alert message.
The main aim of this paper proposes a system to act as a smart mirror which displays date, time, weather update can be collected from internet and displayed in that smart mirror. Today modern world, Intelligent system not only present in the smartphone and tablet-based Computers. In the future more, the intelligent device came into existence. Like that smart mirror also the intelligent smart system. This system is built with raspberry pi, camera, and some sensors it is perfectly suitable for smart homes. Weather reports are extracted from the weather cloud they are Providing API for Extracting the information, that designed smart mirror has the advantage of small size and less weight and more compact to use and it is suitable for families.
The Internet of Things (IoT), as expected infrastructure for envisioned concept of Smart building, brings new possibilities for the building management. IoT vision introduces promising and economical solutions for massive data collection and its analysis which can be applied in many domains and so make them operating more efficiently.
This paper presents an idea to design a Smart Cradle System using IOT which will help the Parents to monitor their child even if they are away from home & detect every activity of the Baby from any distant corner of the world. It is an innovative, smart & protective Cradle System to nurture an infant in an efficient way. This system considers all the minute details required for the care & protection of the Baby in the cradle. The design of smartness & innovation comes with the use of technologies/methodologies which include Internet of Things (IOT) (Modules like Raspberry Pi, Humidity & Temperature sensing), Cry Detecting Mechanism, Live Video Surveillance, Cloud Computing (Data Storage) & User Friendly Web application(for User Controls). In order to detect each & every activity of Baby, different Sensors/Modules are attached to the Cradle: Humidity & Temperature Sensing Module for detection of Wetness of the bed, A Camera on top of the Cradle for live video footage & Cry Detection Circuit to analyze Cry Patterns. All the data which is been taken from the sensors/modules will be stored in Cloud (ThingSpeak) & analyzed at regular intervals. A Health Algorithm is applied to these datasets to get information about the body conditions which is helpful as any regular symptoms of a disease can be identified easily.
Raspberry Pi which having inbuilt wi-fi, which makes Raspberry Pi to suitable for IoT applications, so that by using IoT technology this monitoring system works by uploading the temperature value to the Thingspeak cloud by this project you can able to learn to how to handle cloud-based application using API keys. In this monitoring system, we used Thingspeak cloud, the cloud which is suitable to view the sensor logs in the form of graph plots. Here we created one field to monitor the temperature value, that can be reconfigurable to monitor a number of sensor values in various fields. This basic will teach you to how to work with a cloud by using LM35 as a temperature sensor, to detect the temperature and to upload those values into the cloud.
The sensor DHT11 which is capable of sensing both Temperature and Humidity values. It should be decoded to splitting the two parameters from a single sensor, we are using Adafruit library for decoding values from DHT11 sensor. Sensor values can be read directly from the configured pin used in the program. From this system, we can reduce the hardware requirements, by using a single sensor you will be getting two parameters. It doesn’t require any ADC converters. By using these values any application can be done which requires both Temperature and Humidity.
Examination system is developed a lot; Government and Private organization also do the online examination. To increase further security we are using Web server based E-Exam with Fingerprint authentication to easily go into the Examination, instead of following huge instruction to get into the examination. If the fingerprint matches with the registered user, they are authenticated and time begins with a web server, which prompts the question paper to make them answer using Raspberry Pi. Every examiner fingerprint should be already registered.
MQTT is Message Queuing Telemetry Transport, which is the lightweight protocol, used where the internet speed is low. Since it is the lightweight protocol, it can send a message at quick speed even in low internet speed. When compared to MQTT protocol, HTTP is a heavyweight protocol, by using MQTT, we can transmit short messages. Here home appliances can be controlled using the MQTT protocol.