Application And Application Of Crowdsensing Application

devices to be mobile (Haseeb, 2017). If vehicles or medical devices are remotely taken over by

By completing or participating these tasks, individuals could get jobs, financial rewards, knowledge or experience.（2012）This definition will be further confirmed in following discussion on application examples.

Abstract. In this paper we opt for an experimental approach and used various types of real –world different environment conditions determine the actual power consumption of wireless sensor nodes with different set of batteries for each different environment. We took reading in different environment such as Savage Arena, Auditorium, Lab and parking lot. Some of our observations are close to the previously published papers. We got these results from widely used Zolertia Z1 motes with particular grid patterns. We have compared these results with simulated results in Contiki Os

Sensors with context are core of IoT (Internet of Things) momentum and sensors are going to detect events or changes in the environment. The environment could be your home, city, park, factory, mall or a human body. Sensors could detect changes in your body, blood or tears and warn us about the diseases like diabetes, heart attack or cancer in advanced stages. There are lot of wearables that are equipped with sensors can bring context to the mix to save lives or increase life span.

The impossible measurements in typical ways have currently become attainable using the wireless technology. Wireless sensors are used in most of the in real time applications for collecting physical information. Wireless sensors are spatially distributed autonomous sensors to monitor physical or environmental conditions, such as temperature, sound, pressure, etc. and to cooperatively pass their data through the network to a main location. They are self-configured sensors to monitor physical or environmental conditions, such as temperature, sound, vibration, pressure, motion or pollutants and to cooperatively pass their data through the network to a main location or sink where the data can be observed and analyzed. A sink or base station acts like an interface between users and the network. The main objective of this paper is to introduce air pollution detection using internet of things and to report the status of the air quality whenever needed. This system is low

The introduction of the mobile phone has consequently introduced a number of impacts on different levels. Namely economical, environmental, human health and human behavior. In this report we are particularly concerned with the latest. As mobile use expand among groups and by individuals, the number of features and functionalities within a single handset is also increasing. And with the introduction of new trends, functionalities and social media, mobiles use has thus increased, vice-versa. The integration of built in cameras, location services, wireless

With the rapid growth of the mobile Internet and the mass market of the mobile platform like smartphone, tablets and the laptops create the anytime /anywhere computing and help to increase popularity of mobile Internet applications (Raychaudhuri & Mandayam, 2012).

Technical innovations changed every day life as fast and profoundly as the massive use of personal mobile communications. With rapid increase of modern communications networks, problems like emission of CO2 and energy consumption has emerged which have a potential adverse impact upon the environment and their operating energy costs are also increasing. Since 2006, data traffic on mobile networks has been increasing at a rate of approximately 300% and is expected to grow even at much faster rate. This has forced the researchers to address how to design future wireless networks which can reduce the energy

As previously noted, the worldwide penetration of mobile phone is approximately 93%. This astounding rate includes the number of smart phones which reached the 1.301 billion in 2014 according to “Gartner”* and should attain 2 billion at the end of 2015 according to “Bloomereng”*. Adding to it the number of smart devices as digital tablets, this leads to a breathtaking number of machines which work by the means of applications. Therefore, we can say that each person using mobile phone, particularly smart phone users, is inclined to consume mobile

1.1 In 2008 the number of things on the internet surpassed the number of people utilising it, with an estimate of 50 billion active devices by 2020. The Internet of Things (IOT) consists of any objects such as homes, cars or even walking sticks that are able to register external data and communicate this information, usually wirelessly, it has received via its sensors to other devices. Objects on the IOT will be uniquely detectable and allow users to remotely manipulate them via existing networks which will allow for greater data retrieval that is more accurate and increased efficiency of processes.

Abstract—Location based services and location tacking applications are gaining much popularity among the youngsters and designing such an android mobile application is also expected to have much attraction among users. Designing such an application is our project idea. Although many new applications provide such facilities user’s privacy is not up to the mark. Moreover this location hunter tracks the location of the other user when a call is made, and only those phones in the paired networks will be able to track the location of the target mobile devices. Thus privacy may be provided to the application’s users.

The contribution of this paper is in two ways. We define three algorithms in the OTT VAN architecture which take application type or application quality into account. The objective is to address the application demands to achieve an effective network. We need evaluate these algorithms on a scenario basis. We will have to investigate a user watching a YouTube video clip under varying video quality, while both Cellular and Wi-Fi networks are available. We can evaluate the user aware quality, Cellular usage, and power consumption of the device using test-bed measurements. Cell phones get the energy from the batteries which is needed for their operation. Battery limit is seriously limited because of

Wireless Sensor networks are defined as the distribution of the sensors in the irregular manner. It is a heterogeneous system. The range of sensors used in the network may be from few hundreds to thousands. These sensors will have limited resources like power, storage, communication and processing capability.

A sensor network has large number of sensor nodes, which are appropriately deployed or place either inside the experiment or very near to it. A sensor network is a network consisting of distributed wireless automatic devices using sensors to coordinately monitor physical or surrounding conditions, such as temperature, sound, stress/ pressure, movements or pollutants etc at different locations and time. The development of wireless sensor networks was originally motivated by military applications such as battlefield surveillance. The wireless sensor networks nowadays can be used in many more application areas, including environment and domain monitoring, medical applications, intelligent home systems, and traffic commanding.

As the concept of mobile computing is on the rise. It has led to the new personal computing platform called Smartphone devices. According to (Reddi & Yuhao, 2017), there are more than three billion web-connected mobile devices and by 2020, there will be 50 billion of such devices. Increasing number of mobiles devices are connected to the internet every day and the mobile web traffic is gradually exceeding the desktop web traffic. The future of computing will soon transition into mobile computing leaving behind the traditional computing.