Abstract

The aim of this project is to create an online weather system which enables a user to check real-time weather parameters of a place anytime and anywhere with just a few buttons click. In this project, a weather station will be built to collect weather parameters. Data collected will then store into Google Cloud and analysis of weather will be done. A mobile app or web will be developed to display the real-time weather conditions and users will receive notification as a reminder to get themselves prepared for their plans.

Project Introduction

Weather condition plays an important role in our daily life as weather and climate are the most ubiquitous factors for home and environment planning. Moreover, the tremendous development of Internet nowadays made possible to monitor weather conditions and collect the respective data in-situ. All the objects, sensors and devices can be linked through the Internet to share and analyze the data collected at various locations. The IoT can be much more extensive in predicting and knowing the weather conditions in particular place by connecting this weather station to the Internet.

The climate of Malaysia is so capricious that hard to predict nowadays. As people grow into a developed country with advanced technology to help humanity and bring convenience to the society, it is now the time for the weather broadcasting to be implemented into the mobile phone instead of keep on checking through only television or radio. However, with the mobile weather checking syste, we have in this era still often we see people rushing for schedule under the rain without umbrella; laundries are still showering by rain; home planted plants are wilted due to the hot and dry weather.

Therefore, the objective of this project is to create an online weather system which enables the user to check real-time weather parameters of a place anytime and anywhere with just a few buttons click. On top of that, people will receive real-time notification or reminder to get themselves prepared for their plans in the current weather.

Figure 1: Overall flow of project

Figure 2: Project architecture

Favoriot platform is chosen because it is a new cloud-based platform designed for IoT which supports the integration, collection, and storage of data from several devices into the internet. It has a scalable big data storage. It also helps developers in building vertical applications to display data in many forms. Favoriot platform is suitable to be used in this project that needs several functions provided in this platform in order to obtain desired results.

Design Methodology

There are three phases to achieve the stated objectives above:

Weather station design and prototype development

These weather parameters are measured using Sparkfun Weather Shield sensor and the Raspberry Pi 3 with built-in Wi-Fi is used to capture all the data from the weather sensor. The measurements taken include temperature, humidity, atmospheric pressure, light intensity, wind speed and direction, and rain precipitation.

Transferring data to initial state cloud platform

Raspberry Pi 3 will stream the data directly to the cloud. Cloud platform that are suggested to be used in this project are Favoriot because it fully managed data, supports monitoring, logging, and diagnostics, data analysis and helps developers in building vertical applications.

Application of Internet of Things (IoT)

A stream of weather parameters/information can be displayed in a professional graphical fashion which can be accessed from mobile phone or web. Favoriot also allows the development of next generation of applications of the web that is reliable, fast and engaging. Real-time notification will then be sent to the user as a reminder.

Preliminary Result

The SparkFun Weather Shield with built-in Si7021 humidity/temperature sensor, MPL3115A2 barometric pressure sensor, and the ALS-PT19 light sensor was connected to Raspberry Pi 3 as shown in Figure 4.

Figure 4: The hardware of this project

The weather parameters such as temperature, humidity, and pressure are taken from the weather shield and loaded into Raspberry Pi 3. The weather parameters were displayed at the Lx terminal of the VNC viewer as shown in Figure 5. Data collected from the sensors were successfully streamed into Favoriot and shown in the dashboard as shown in Figure 6. However, the data streamed into the Favoriot is not tally with the data collected from the sensors as for now.  In addition, the current weather conditions are updated to multiple social media every hour to notify the user as shown in Figure 7. The number of update post can be determined by modifying the python code.

Figure 5: The weather parameters displayed in Lx terminal of Raspberry Pi 3

Figure 6: Data is being streamed and displayed in Favoriot

Figure 7: Twitter post showing the current weather condition

Expected Result

The expected results toward the end of this project are described as below:

Prototype

A prototype of weather station by using Raspberry Pi 3 and Sparkfun Weather Shield sensor is designed and developed for climatology monitoring. The weather station is able to be interfaced to the Favoriot cloud platform. Weather parameters are able to be collected and saved in the cloud.

Application

Weather parameters can be analyzed online with graphical presentation. People can access the weather-related information via mobile phone or web easily. Notifications will be sent to the users too as a reminder.

Figure 8: Expected results of Favoriot data analytics for weather parameters in (a) line chart and (b) column chart.

Figure 9: Expected results of weather app development using Favoriot platform

[Note: This project is being done by UTHM, our FAVORIOT’s University collaborator. Article was written by Pui Yan Muck]

You can check out the whole LIST of IOT PROJECTS by our University Collaborators.

Malaysia needs a pool of Generation-IoT to propel into the era of the Internet of Things and turn the National IoT Strategic Framework into a reality. We need about 100K of IoT workforce which is more than the target as stated in the Framework because to support the whole value-chain of IoT. But how do we groom the workforce of the future? How do we inspire and prepare them for the jobs of the future? Are they ready for the Fourth Industrial Revolution? UTM has invited FAVORIOT’s CEO, Dr. Mazlan Abbas for an Industrial Talk on the topic of “Journey Towards Industry 4.0 With IoT“.

Thus, on behalf of the Faculty of Electrical Engineering, Universiti Teknologi Malaysia, Advanced Telecommunication Technology Research Group (ATT RG) in collaboration with Communication Engineering Department will organize the Internet-of-Things (IoT) Carnival 2017. The event is part of UTM’s Corporate Social Responsibility (CSR) program to promote exposure and awareness to Science, Technology, Engineering and Mathematics (STEM) education which is in line with the Government’s National STEM Action Plan 2017 initiatives.

The main objectives of the IoT Carnival:-

• To expose the Internet-of-Things (IoT) technology to the guests, UTM staffs, and students.
• To encourage UTM students, especially the undergraduate final year students to further their studies in IoT-related fields at FKE UTM.
• To promote IoT-based products, including research findings, final year projects, and related capstone labs projects.
• To provide the opportunities for research collaboration between industries and researchers with ATT and COMM department, as well as FKE in general.
• To help promote National Transformation 2050 (TN50) roadmap initiatives in preparing the people for Industry 4.0 of which IoT technology is a crucial element

[Original article published by Tan Chin Luh – “When Machine Learning Meets IoT“]

In our upcoming training “IoT Made Easy with Favoriot and Scilab IoT Module“, we will be building an IoT system prototype by using a simple Machine Learning example.

Loading Data Set

The dataset consists of 2 sensors reading, one from the light sensor, another from the voltage divider with a variable resistor.

The idea is pretty simple: Turning on LEDs or sound the buzzer when the 2 sensors are falling in the region of the “blue dots”.

Training The Neural Network And Visualizing the Decision Boundary

The data is feed into neural network provided in Scilab Neural Network Module and trained for classification purpose. The result is shown as below:

Testing with Arduino and Gadgets

The simple system as below is built and interface with a computer to test the neural network in real-time.

The video below illustrates the result when the sensors reading (red circle) reach the “blue dot” region, the buzzer will beep and the LEDs would be turned on, and off when it reaches the “green star” region.

Trying With Data from MQTT Server

Finally, we will try it out with the signal from the MQTT server!

Join Us At:

IoT Made Easy with Favoriot and Scilab IoT Module Training

FAVORIOT offered a very affordable pricing plan as shown below:

The Beginner Plan is very suitable for University students who have been assigned or chose IoT project as their Final Year Project. A single device such as Raspberry Pi or Arduino that collects from several connected sensors can stream to the IoT platform. A simple dashboard is provided to visualize the measurements. This plan is also suitable for an individual developer or hobbyist that would like to familiarize with IoT platform, conduct self-learning or participate in IoT Hackathons. At RM 8.33 (or less than USD 2.00) per month, you can become the next Generation-IoT and on your way to be one of the rare talents in the job market today!

The Startup Plan is perfect for Freelancers or SMEs or Startups to provide IoT solution for a medium size project up to 150 devices. In fact, they can also create multiple projects or applications but limited to the total number of 150 devices.

The Business Plan is great for developing big commercial IoT project. It can support up to 300 devices for many smart applications.

However, if a company requires connecting thousands of devices, they may contact/email their customized requirements to sales@favoriot.com

CLICK HERE to Subscribe/Request for Quotation.

Check out the COMPLETE Tutorial How to connect an Arduino to FAVORIOT Platform. You can also download a STEP-by-STEP Tutorial –  TUTORIAL – Cytron Uno with FAVORIOT Platform (53 downloads)