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.
Some Apps are already build around this in India, but typical problem is poor response and no accountability from Civic authorities to resolved the issues in time bound manner, as there is no SLA or punitive action proposed against them.
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.
The post Opportunity to CrowdSense Billions – Internet of Human Sensors (IoH) first appeared on RiseOfMachine.com
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