Friday, 22 April 2016

Yuktix python library to get Bangalore weather network data

Here we are releasing our python library for accessing Yuktix public API. This release is limited to weather network and public API only.

You can access the public API doc from here . Yuktix public API are REST API and of course you can write a client in your favourite language. All you need is your public API access key that you can see on your account | profile page.

This is a wrapper built using Request library ( and tested with Python 2.7.11. The full code is available as Gist right now. I will do better packaging and check it in a Github repo as well. I know all about API abuse. we are a small team and the only time I get to work on such stuff is between 12:00-3 AM so please play nice!

The Library

The script

Bangalore on boil at 40C - April update

The Picture says it all. 

Temperature data from 7 stations across Bangalore shows the maximum temperature rising towards 40C. see the difference between 1st week of April and the third week.

 Here is the Max temperature sand worm digging up towards the surface! The big dip is due to Thejesh station at EC going offline on 5th and not recording day time temperatures because of UPS failure! switch to Solar, I say!

  One question you always ask is, am I recording what I am recording? Big effects should show across all the stations and looks like something happened on 6th. All stations are in tandem!


Thursday, 7 April 2016

Bangalore is getting hotter - march 2016 vs. 2015 temperature data in pictures

We record temperature data across the city and here we show graphs from two stations, one inHSR Layout and another in Jayanagar 4th Block.  Raw data from more stations is attached for intrepid folks. We show the trend for minimum, maximum and average temperature plotted across days in march 2015 vs. march 2016.

First, the Jayanagar station.

Both the minimum temperature as well as Maximum has gone up so no cheating averages here. The days were actually hotter on the whole! Maybe I will plot raw data across too instead of aggregates just to get the kicks. Interesting data is that first half of march was lot hotter compared to second half.  Last 5 days the temperatures actually come closer together. The spread in average is a good deal of 3-4 degrees centigrade.

Now the HSR station

Look at the max and min. here too! The spread is 5-6 degrees more than the last year! Should we say that HSR in first half of march in 2016 was 5 degrees hotter than 2015? 

As a bonus, the raw data points for 4 stations are attached. Usual caveat emptors apply.  The zero points are because of errors in parsing floating points. I will fix the script. (someday...)

Update: Scroll has published an article on Hot Bangalore

Monday, 4 April 2016

Noise Pollution and its effect - Part 1

Noise Pollution, sources and its adverse effects - Bangalore 

Working in a start-up and like Yuktix which is into IOT (Internet of Things) for Environmental monitoring and Agriculture means a lot of field trips across the city to the remote places in Bangalore. Also now days, every job is stress full and not because of the work pressure but because of many other factors like traffic, pollution(air, sound). And when you cross some of the most busiest junction of the city like silk board and some one just behind you honk with out any reason, just like he is on a F1 race track, you feel getting out of your car or scooter and say ******* ? Wait !!!! what is it, feeling too much annoyed on some one honking behind you is a  symptom of you being in stress and tension.

Bangalore - IT capital 
Bangalore is IT capital of the nation and the top most city giving birth to new start-ups and  rise to number of job opportunities in the cities and thus leads to migration of people from different part of country to Bangalore. As per daily newspaper The Hindu, there are 55 lakhs vehicles plying on the roads of Bangalore with a average speed of 15km/hour which as per observation is going to decrease further to 9-10km/hour.

image source - The Hindu 
With these much vehicles on the road and even 10% of them or 1% of them honking, one can assume amount of noise pollution, but we can never say as we don't have any real time data. Although Government of Karnataka via KSPCPB(Karnataka state pollution control board) has installed 5 continuous monitoring station at BTM layout, Marathalli, Nisarga Bhavan, Parisara Bhavan and Pinia.  Below is the snapshot of the noise pollution for the year 2013-14.

Image source - KSPCB
By the year 2014-15, 5 more station have been installed in Bangalore in sensitive areas's and they are NIMHANS, RVCE Mysore road, TERI office - Domlur, White filed industrial area, Yeswantpura Police station.  Here is the data collected from these sensor's. link As per CPCB, in industrial areas, the maximum allowed limit is 75dB in the day and about 70dB at night. Similarly, in residential areas the (permitted) limit is about 65dB in the day and 60dB at night, and in areas which qualify as silent zones, like areas surrounding hospitals, the prescribed upper limit is about 55dB in the day and 45dB at night. 

There are multiple sources of noise pollution and major among them are
  1. Industrial Sources 
  2. Transport, Public and private vehicles 
  3. Household 
  4. Public address systems 
  5. Defense equipment 
  6. Crackers and Aircraft noise 
Adverse effect of Noise pollution 
Frankly, the biggest and the strongest effect of noise pollution, i see is stress, aggression and hypertension. Even sometime, ,i feel the effect of the same. In this busy life of IT and digitization, when everyone is too much busy, there is always a stress factors added to it. With noise pollution it always increase. Below are some of the adverse effects of noise pollution.  Noise levels above 55dB are sufficient to cause annoyance and aggressive behavior. Also sound level above 75 dB can lead to increased stress levels, increased heart rates and potential hearing loss. 

  1. Annoyance and Aggression 
  2. Hypertension
  3. High Stress level 
  4. Tinnitus
  5. Hearing loss
  6. Sleep disturbance
Here is link to small article on the ill effect of noise pollution on the health of Traffic cops in Bangalore. Most of the cops suffer from tinnitus. Also as per this article, Bangalore stand at second place with 1906 suicide cases in 2014 and hypertension, stress might be the reason for the same. So what is the need of talking all about it here. Point to be taken from here is, Noise pollution is one of the stress inducing factor in daily life of people living in metro cities who already have lot of stress in their life. 

Why real time monitoring?
Suppose you are moving through some of the busiest junction in the city, being inside the car, you don't care if anyone or even you are honking or not. Or even a administrative officer in Karnataka government get real time update on his mobile if any of the units find more than allowed, then atleast traffic cops can take some preventive measures. And the biggest things is awareness among the people. Data which is not public is of no use. These days with social media, its lot easier to distribute data and make people aware. Once people are aware of the levels of noise and its ill effetcs, they themselves will stop honking. 

Yuktix has developed in-house highly sensitive ambient noise sensor capable of measuring noise from 0-120 dB SPL RMS DC values. 

These sensor when  plugged with Yuktix IoT (Internet of thing) platform will turn into real time noise pollution monitoring station capable of running on both solar power and AC power. Data from these units would be published on the Yuktix Cloud which would be open to public as well as on Android application. 


We are trying to partner with some NGO's and companies working towards social cause in installing these real time ambient noise monitoring stations at some of the busiest junction across the city. Very soon we will be publishing a article with more data about our Ambient noise sensor, its sensitivity and comparison with other available DIY sensor. 

Saturday, 12 March 2016

Digitizing Indian Agriculture Institutes - Using Yuktix IOT platform - Part 2

Digitizing Indian Agriculture Institutes - Using Yuktix IOT platform - Part 2 - Installation. 

Today, Yuktix team finished up installing off-grid, solar powered Automatic Weather station and Air quality station at one of the Agricultural institute based out of Bangalore. In all, there are net 16 sensor installed in the site and it is 1st of its kind of installation by Yuktix Technologies. Along with Automatic Weather Station and Air Quality Station, a quad-copter fitted with a wireless camera is also supplied to the institute. There is further talk of how to effectively use the live feed of wireless camera in generating NDVI imagery which can be very useful for a agriculture institute in knowing the "greenness" or photosynthetic activity. 

In our last blog, we talked about how we are digitizing Indian Agriculture institutes with Yuktix IOT platform. For any IoT platform, data capturing from the physical environment is one of the major part and that is done using multiple available communication options. In our case we have use GPRS for posting captured data from the environment to the  Yuktix Cloud. Below is small pictorial description of how we do that. 

Sensor's in this case are 
  1. Atmospheric Temperature
  2. Relative Humidity
  3. Pressure
  4. Rainfall
  5. Wind speed
  6. Wind direction 
  7. Leaf wetness
  8. Soil Dielectric Permitivity (using TOPP's equation, we can find out moisture for different type of soils.)
  9. Soil temperature
  10. Solar Irradiance
  11. CO
  12. CO2
  13. NH3
  14. PM2.5
  15. PM10
  16. And Ambient Noise
Below are some of the photos of our present installation. 

Data from above mentioned sensor are captured by Yuktix device and pushed to Yuktix cloud via GPRS where it is stored in a time-series database . Once data is stored, it is then displayed on Yuktix Web-application in real time with in different forms. You can see data for 
  1. For part 6 hour in raw format.
  2. For past day (average of one hour) and 
  3. For past week. 

You can even scroll and see the past data. We even provide the raw data stored in our archive, so if any researcher is interested to do his/her research, he can use raw data available in .xlxs format or .csv format. We even have public and private API's, which can be used to fetch data from our server and thus any one can use our data. Data from our servers can also be ported to other clouds, so there is no data silos. There are lot of other features of Yuktix cloud, which we will be discussing in our other blog. 

Along with all above mentioned features of Yuktix IOT platform, Yuktix Android application is yet another important feature. In our present installation, we have used Android OTT to deploy our application in the institute and institute has become one of first of its kind of Institute to use such technology to display weather related information in real time in their premises. Below are some of the pics while we were testing the OTT box in our office and while we were installing the TV in institute premise. 

And this is how, we at Yuktix Technologies provide end-to-end complete IoT solution for Indian Agricultural Institutes, so that they can get data in their office in real time without putting much of the effort. 

For more information on the project, you can drop us a mail at or 

Friday, 19 February 2016

Digitizing Indian Agriculture Institutes - Using Yuktix IOT platform.

Digitizing Indian Agriculture Institutes - Using Yuktix IOT platform - Part 1

During our first visit to one of Agriculture institutes based out of Bangalore, we were told a problem which they were facing in getting access to the Automatic Weather station data from the servers. Their Automatic Weather Station use K-band satellite communication. 
(1) Process take a long time to access the archive of past data. 
(2) Login details were not shared with them 
(3) No analysis of data. 
(4) No customization as per their needs. 
(5) Data aggregation is a problem. 
And thus they were based on a manual weather station observatory. They use to take 2 readings per day, share the same reading with IMD (Indian Meteorological department), get the weather forecast and share the weather forecast with the farmers.  And problem with taking 2 readings in the day is that there is lot of variation of weather parameters during  the whole day, increasing frequency of data capturing can resolve the problem. 
This is where Yuktix Automatic Weather Station come into action. We started developing Automatic Weather stations around Yuktix IOT platform for a weather enthusiasts based out of Bangalore facing the same problem of getting access to weather data from IMD. The project was named as Bangalore Open weather project. You can access the same .
You can read more about the project at Knowyourclimate blog and at this link.  At present we are running 18 weather stations in Bangalore and Mysore. We deployed fully solar power Automatic Weather station at the same institute with 10 sensor. Yuktix Automatic Weather station, sample environment data after every 15 second, take a average and send it to server after every 3 minutes, thus not missing even the smallest change in the weather. 
How it solve the problem :
(1) Now without going to observatory in person, they now get the real time data on their screen. 
(2) They can get access to the raw data from Yuktix Archive for their research. 
(3) Customization is easily possible on what to show and what not to. 
(4) Analysis of received data, like hourly average, Daily average, Mix, Max and Average is possible. 
(5) Data is displayed using Graphs for last 6 hour, last day, last week.
You can read more about Yuktix Cloud features at this link. The best part of Yuktix Automatic Weather station is that it's a complete package of Hardware (Data acquisition unit and sensors) , Cloud server (Yuktix Cloud), Web-app (Yuktix Web app) and Android application (Yuktix Android application). We have developed a new application for one of the premier Agriculture research institute based out of Bangalore and very soon we are going to deploy a set-up of 15 sensor in their campus. 
So this is how we are going to digitize the process of data capturing, analysis and display using Yuktix complete IOT platform. Below is the image of android app displaying all the stations on a 49" LCD TV.
Yuktix is using the same IOT platform in the field of environmental monitoring (Air quality) for smart cities,  Greenhouse internal environment monitoring and in different other fields of Agriculture. 

Tuesday, 9 February 2016

Air Quality in Indian Cities - Part 2 - AQI and what to measure

Air quality Index (AQI) and what to measure - Particles and Gases

This is second article in the series of articles Yuktix is publishing on air quality. First part of this series looked at the requirements of measuring air quality in Indian cities. We tried to answer why we should measure air quality and how we can develop a plan to do so on a budget. Here in this article, we look at what variables to measure and what comprises air quality index and how we should report and interpret it.

The best place to look for information related to air quality is US environment protection agency (referred to as EPA in this article).   There are many gases and different types of particles present in the environment around us. Most can have harmful effect on humans in higher/lower concentrations so it is important to know what we want to measure under ordinary circumstances, e.g. when we are walking on the road or sitting on porch sipping coffee.

The Air quality index (AQI) of EPA, USA comprises of following six pollutants

  1. PM 2.5 (particles less than 10 microns) 
  2. PM 10 (particles less than 2.5 microns) 
  3. NO2 (Nitrogen Dioxide) 
  4. SO2 (Sulphur Dioxide) 
  5. CO (Carbon Monoxide) 
  6. O3 (Ozone) 

The EPA site has a wealth of information and there is no point in repeating that here. EPA site also has AQI calculators, sources of pollution and their effect on humans. 

Government of India Air Quality index comprises of above six and also 

  1. Ammonia (NH3) 
  2. Lead (Pb) 

The ministry of Environment, Forest and climate change links to an IIT Kanpur website that of course, does not work so we are trusting the Wikipedia link.

We first quickly summarize the risk of individual pollutant on humans, their possible sources and then move on to AQI.

Carbon Monoxide (CO)

Carbon monoxide (CO) is a colorless, odorless gas emitted from combustion processes. Nationally and, particularly in urban areas, the majority of CO emissions to ambient air come from mobile sources. It forms when carbon in the fuel does not completely burn. CO can cause harmful health effects by reducing oxygen delivery to the body's organs (like the heart and brain) and tissues. CO can cause issues with mental alertness and vision. At extremely high levels, CO can cause death. Indian cities can have CO from vehicle exhausts, burning coal and wood, furnaces and Diesel generators.

Ozone (O3)

It is hard to believe that ozone can be bad when we all know about the role it plays in shielding us from harmful UV rays. However Ground level or "bad" ozone is not emitted directly into the air. Bad ozone forms when pollutants emitted by sources such as cars, power plants, industrial boilers, refineries, and chemical plants react chemically in sunlight. Breathing ozone can trigger variety of health problems, particularly for children, the elderly, and people of all ages who have lung diseases such as asthma.

Ozone can aggravate asthma and even cause permanent lung damage.

PM 2.5 and PM 10

  • Typical human hair width 17-180 micrometers
  • Average human hair width 70 micrometers
  • Resolution of Human eye - 90 micrometers
  • PM2.5 - particles less than 2.5 micrometers
  • PM10 - particles less than 10 micrometers

PM2.5 and PM2.5 refer to particles that are very small and you cannot see them with naked eye. Particles smaller than 10 micrometers in diameter can cause or aggravate a number of health problems and have been linked with illnesses and deaths from heart or lung disease.

The reporting for particles is usually done in two ways.

Better or more sophisticated instruments actually catch and weigh the particles of a particular size. The instrument will catch particles over a sampling period in a volume, weigh them and report the concentration as micrograms/cubic meter (Ug/m^3).

Simple instruments report number of particles found in a particular volume. They don’t have the mechanism to actually weight the particles. That volume is usually reported in 0.01cf (0.01 cubic feet or 283 ml). So you will see reporting done as 2000/0.01cf or 283 ml. That means the instrument has detected 2000 particles below this particular size in a sampling period in 283ml volume.

PM10, PM2.5, PM1 are not different things but 3 different metrics of the same aerosol population. The reasons for using one over the others are largely historic as there is loads more info on PM10 than there is on PM2.5 and on PM1 but these are all indicators and not in themselves the goal of any measurement.

Fine particles (PM 2.5)

The smallest particles (those 2.5 micrometers or less in diameter) are called “fine” particles. These particles are so small they can be detected only with an electron microscope. Major sources of fine particles include motor vehicles, power plants, residential wood burning, forest fires, agricultural burning, some industrial processes, and other combustion processes.

Coarse particles (PM10)

Particles between 2.5 and 10 micrometers in diameter are referred to as “coarse.” Sources of coarse particles include crushing or grinding operations, and dust stirred up by vehicles traveling on roads.

Sources for PM2.5 are

  •     Acids
  •     Organic chemicals,
  •     Metal,
  •     Dust particles
  •     Gases from automobiles
  •     Industrial pollution

   Sources for PM10

  •  Dust
  •  Pollen
  •  Mold

Nitrogen dioxide (NO2)

NO2 is one of a group of highly reactive gasses known as "oxides of nitrogen," or "nitrogen oxides (NOx)." NO2 forms quickly from emissions from cars, trucks and buses, power plants, and off-road equipment In addition to contributing to the formation of ground- level ozone, and fine particle pollution. NO2 is linked with a number of adverse effects on the respiratory system.

Sulphur dioxide

SO2 is one of a group of highly reactive gasses known as “oxides of sulphur.” The largest sources of SO2 emissions are from fossil fuel combustion at power plants (73%) and other industrial facilities (20%). Smaller sources of SO2 emissions include industrial processes such as extracting metal from ore, and the burning of high sulphur containing fuels by locomotives, large ships, and non-road equipment. SO2 is linked with a number of adverse effects on the respiratory system.


Ammonia is a colorless gas with a pungent odor that is noticeable at concentrations above 50 ppm. Most of the NH3 emitted is generated from livestock waste management and fertilizer production.

Ammonia is poisonous if inhaled in great quantities and is irritating to the eyes, nose, and throat in lesser amounts. It combines in the atmosphere with sulphates and nitrates to form secondary fine particulate matter (PM2.5). PM2.5 is known to have harmful effects on human health and the environment. NH3 can also contribute to the nitrification and eutrophication of aquatic systems.

Lead (Pb)

Lead (Pb) is a metal found naturally in the environment as well as in manufactured products.  The major sources of lead emissions have historically been from fuels in on-road motor vehicles (such as cars and trucks) and industrial sources

Lead exposure can happen from air pollution (vehicle exhausts), lead in drinking water supply and lead contaminated food.  Once taken into the body, lead distributes throughout the body in the blood and is accumulated in the bones.  Depending on the level of exposure, lead can adversely affect the nervous system, kidney function, immune system, reproductive and developmental systems and the cardiovascular system.  Lead exposure also affects the oxygen carrying capacity of the blood


Air quality index (AQI) is an effort to map the different units of measurement and ranges into a friendly number scale. To illustrate, we could have reported air quality information as

  • CO – 35 PPM
  • O3 – 75 PPB
  • PM2.5 -- 10 ug/m^3 to 100ug/m^3
  • PM10 – 10ug/m^3 to 100 ug/m^3
  • NO2 – 100 PPB
  • SO2 – 100 PPB
  • Lead  - 0.15 ug/m^3

Here gases are reported in parts per million (PPM) or parts per billion (PPB). There are different acceptable ranges for different gases, e.g. CO at 10 PPM is not hazardous but NO2 at 10 PPM is hazardous.  Also, the numbers do not indicate whether the concentrations are hazardous or at moderate levels.  

For quick reading, we need a system where we can map full concentration range onto a number scale so we can say something like

CO – 0-10 PPM – OK   1 on Danger scale
CO – 10–35 PPM – Not OK but can tolerate – 2 on Danger scale
CO – 35–70 PPM – NOT OK, approaching hazardous levels – 3 on Danger scale

Then we can render the information as

1      Green  - 1 
    Yellow - 2   
    Red - 3 

    Dead - 4 

There is nothing magical about EPA 0-300 scale.  They might as well have had 0-10 or 1-5 scale. There in the report, you have a number and that number means a concentration of particle or gas. You can convert from AQI number to concentration using a calculator

Most people are likely to follow EPA reporting standards

  • Good – 0-50
  • Moderate 50-100
  • Unhealthy 101-150
  • Unhealthy for everyone 151-200
  • Very unhealthy 201-300

AQI is not like stock market index

AQI is concentration to number translation for a pollutant in the index. This is not a weighted or average index like a stock market index. That is why you have separate AQI number for every pollutant included in the index. AQI is “index” in the sense that you have an index of “pollutants”.

So at least in theory you can have safe AQI numbers for pollutant A and hazardous levels for pollutant B. Tomorrow it may as well happen that Government of India decides to create their own AQI index.  They may as well say that in India, CO till 35 PPM is Level 1 and after 70 PPM is level 2 etc.

Third part of this series will look at how to measure particles and gases. We will try to demystify the terms and jargons. We will look at typical sensors deployed to measure particles and gases and what can be done to make a sensor cocktail on budget.