In my earlier article India is betting high on IoT
,we touched upon how IoT based solutions are advantageous for rural
areas of India as well as they are converting the Urban cities and rural
villages to smart cities and smart villages respectively by providing
them access to various technologies. This is basically working on the
concept of empowering millions in India and “connecting humans”
to the main stream. This article will establish the meaning of
connecting humans and how can we become millions humans to empower
citizens.
Less than 30% of India’s 1.3 billion
population use the internet. As per ASSOCHAM, the estimated number of
smartphone users in India will be over 600 million by 2020, a near
three-fold jump from the current figure of slightly less than 200
million in 2016. Internet have been human to human affair but that is
changing, where Internet of Things (IoT) is everything to everything
communication. There will be 10 connected objects for every man, woman,
and child on the planet. Giving us the opportunity to connect in ways we
could have never dreamed possible. With the use of power of smart
devices, people will not only consume data, but contribute observed data
to the IoT through crowdsourcing from their phones and tablets as “human sensors “.
Crowdsourcing is a way of acquiring
services, ideas, and valuable data from a group of people. This
volunteering process or labor division can help into segmenting and
solve big problems like another divide and conquer method.
In the recent years, smartphones have
become essential for our day life. They are normally equipped with a
rich set of sensors, including GPS, microphone, camera, accelerometer
and gyroscope among the
others. Consequently, everyone can easy
collect and share sensing information through crowd-sensing.
Crowd-sensing is the same principle as crowdsourcing i.e. data is
acquired by devices or sensors. Mobile crowdsensing emerged recently as a
promising large-scale data sensing collection paradigm where the
collection is usually performed by smartphones. The wide availability of
sensing modules in mobile devices enables social networking services to
be accessed and extended to incorporate location based services, media
tag services, etc. Data is then shared and sent to a central collector
running in the cloud. Mobile crowdsensing is projected to become one of
the most important technologies contributing to future smart cities.
There are several sources of mobility sensing data originated at mobile devices, classified as:
- Physical sensors,
- Virtual (logical) sensors,
- Social sensors.
Physical sensors
include sensors integrated in, or attached to mobile devices (smart
phones, tablets, etc.), such as: GPS, microphone, camera, ambient light
sensor, accelerometer, gyroscope, compass, proximity sensor and the
temperature and humidity sensors available on advanced smartphones.
The development of wearable and pervasive systems, such as Sensordrone and iWatch2,
provides integration of additional sophisticated sensors, worn by users
and attached to their mobile devices, to measure air pollution,
personal health parameters and the emotional and physiological status of
users.
Virtual sensors are
not hardware sensors but software applications that run at user devices
and collect information about users, their profile and preferences,
detecting their context and situation. Such sensors detect information
related to user communications (voice, SMS, etc.), user activities and
interaction with devices (active applications, application in focus, the
type of the interaction, etc.), user preferences and profile,
user-generated content (texts, speech, videos, photos, sounds), etc.
Virtually sensed information is referenced in space and time and
attached to a certain location, symbolic or geographic. For example Walnut Android App
analyses your SMS inbox on phone and detects important information like
spends, bills and tickets. Walnut is the money manager app to
automatically and securely track your monthly spends & pay bills on
time. Find out your spends on categories such as food, travel, shopping,
etc. and how your expense patterns have changed over time.
Social sensors detect
user social status and activities, social network and social media
interactions (tags, likes, Tweets, photos, etc.), currently connected
friends and their status, connections in vicinity, etc. Some of such
information can be detected by accessing social network/media services
through appropriate APIs. In Zurich, Xeebel provides “HeatMapz”
for a mobile mood barometer for nightlife. For this, the status
messages of the party goers are analyzed and visualized. In another
example, London Ferris wheel on the banks of the River Thames during the
Olympic Games. The tonality of tweets was reflected in terms of
Olympics, Torch Relay, or London 2012 in the colors yellow (positive),
green (neutral) or violet (negative).
By empowering the citizen to Sense and make them Smart Citizens , we can achieve the objectives of Smart Cities.
For example City Municipal App can used
Citizens as our Eyes , where they can report crime and other city wide
incidents, need civic authorities attention.
Google Traffic map is one of another
example of using virtual sensors, Traffic density is gathered via crowd
sourcing from smartphone users using Google Maps on a mobile application
in a route. In a nutshell, Google is analyzing the GPS-determined
locations transmitted by a large number of smartphone users as one of
the input to decide the traffic ocndition. By calculating the speed of
users along a length of road, Google is able to generate a Live Traffic
Google Map.
So we can understand that the ‘human
sensor’ data, data crowdsourced from a variety of social networks, has a
number of advantages over traditional sensor information. The first is
that it is completely free and requires no infrastructure other than
existing mobile networks, so it can be used by anyone, today, with no
setup or rollout costs.
The second advantage is that “the human
sensor cuts out noise automatically.” What this means is unlike
traditional sensors, which will keep sending data regardless or not of
whether it has value, human sensors tend to home in on things that are
of interest to humans.
The Londerzeel blaze is
a good example: there were not that many videos of the industrial
estate until it caught fire, and then the images focused on the flames
themselves rather than irrelevant parts of the surrounding area.
Finally, a third advantage of human
sensor data is that it comes with built-in intelligence that you can use
for sophisticated planning and research purposes. This functionality is
already being exploited via online polling platforms such as MyGov.in .
Just how much these benefits can add up
to has been shown in Jakarta, Indonesia, where smart city planners have
placed the human sensor at the center of their innovation strategy.
Jakarta’s smart city platform includes tools such as an issue-reporting mobile app called Qlue, a Twitter-based flood map, and crowd-sourced traffic management system. None of these tools have required an expensive sensor rollout program.
A more harrowing application is underway in the Middle East, where citizens have been enlisted to take photographs as part of a project to create a digital record of monuments under risk of destruction by the Islamic State of Iraq and the Levant.
Despite these real-life uses, experts
admit that in most cases human sensor information can at best complement
traditional Internet of Everything technology, rather than replace it.
Upcoming articles will cover many details of many more crowd sensing applications and related topics.
Feel free to share your comments or suggestions below.
Note : Article captures personal view of author
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