Current State of Mobile Crowd Sensing - Essay Example

Current State of Mobile Crowd Sensing The today’s world has revolved to the extent of many people are involved in the use of mobile and computing devices. They apply the mobile and computing devices in the collection and sharing of data concerning the user or physical world. These devices have been connected to the internet and include smart phones, music players, sensing devices in vehicles and gaming systems with sensors. These devices have gain popularity and have developed to be important sensor data sources. The devices consist of certain sensing equipment and wireless power that make it easier to develop and upload data to the internet (Ganti et al. Page 32). The mobile devices are equipped with various communication computing and sensing systems. They boost the functions of the daily life objects or involved in the collection of information from the environment by themselves. These devices have got applications in all sectors of the economy including health sector, industrial sector, agricultural sector and education sectors. Information sharing and updating have become easier and the information have been of high quality. The paper therefore discusses in broad the current state of art of mobile Crowdsensing looking into the current application in technology. It also discusses the possible future advances and challenges facing this technology. The mobile crowdsensing applications falls into two broad categories considering the type of facts that are analyzed; personal and computing sensing. The application on personal sensing is directed towards the individual. A good example is examining the movement of individuals especially during exercise to determine his or her health status. Another example is the one that examines the method of transportation of an individual in order to get the carbon footprint of the person. Community sensing involves examination of facts that cannot be carried out by one person. A good example is the examination of level of air pollution or traffic congestion. It has therefore been made easier to carry out self or community assessment. One can easily identify and know the body status and decide on whether to seek medical assistance at certain times (Ganti et al.Page 32). The current state of art of mobile crowdsensing has shown its applications in various sectors in the world. Its application has been seen in the environment, infrastructure and social applications. The environmental applications involve the natural environment including examining pollution levels, wildlife habitats and levels of water. These applications involve looking the facts in the environment at a large and involving the main person. A good example is the use of Common sense device in the examination of pollution in the environment. It constitutes sensing devices for examination of quality of air through Bluetooth communication with mobile phones, measuring the level of air pollution. These devises measures the quality of air of a large population when set out in the areas occupied by the population. This is important in the conservation of the environment. Humans can also identify and avoid areas that are highly polluted. The mobile phones or consists of microphones which one can use to measure the noise level of a population. Knowing the level of noise in a population is crucial to avoid causing the damages to our ears. This device is important in the streets especially for the government when implementing laws to monitor noise which is usually believed to be causing commotions in the streets. Creek Watch has also gain popularity in its application in the measure of levels of water in Creek with individuals taking photos of different locations within the Creek and sending text messages concerning the amount of trash available. This information is important to the water board as it can be used for the monitoring and controlling the rate of pollution within the water sources. Controlling water pollution conserves the aquatic life and also minimizes waterborne diseases which are usually brought about by water pollution (Ganti et al.Page 33). Applications in infrastructure benefit broadly the public infrastructure where it requires the examination of large scale facts. It is applied in the examination of public congestion, available parking, conditions of the roads, and identification of old public works and the tracking of transits exact operation time. Car Tel used unique devices that were incorporated in the cars to examine the speed level of these vehicles which were transferred by Wi-Fi hotspots to the central server. The information in the central server was later on used to find out more concerning routes and vehicles. This allows for carrying out of survey or statistics concerning vehicles easier. Nericell also applied the mobile phones of the individuals in the examination of average speed, impediments in traffic and identification of potholes and beeping on roads. Park Net also applied equipment of ultrasonic sensing to identify parking places. These devises were incorporated in the vehicles and smart phones. It is therefore easy for one to know where to park especially in a new street (Ganti et al.Page 33). Social application involves the sharing of meaningful information among the individuals. Individuals may decide to share data concerning their exercise and compare it to the data of their colleagues. This information is important for improvement of exercise. Good examples of the devises applied in the social settings are the Diet Sense and Bike Net. Diet Sense involves individuals sharing the photos of their diet and compare with the diet of their colleagues. This is beneficial especially in the control of diseases such as diabetes where individuals come to know what the other diabetic patients are taking as a diet. This also made it easier to monitor ones diet and prevent predisposing factors to diseases like diabetes or cancer. Bike Net requires the individual to obtain the quality of bike route and location and applied the data in the identification of best routes for biking. This is important best especially when one is under an urgent situation and wants to avoid barriers like traffic jams (Ganti et al. Page 33). The mobile devices in the recent world are equipped with various communication, computing and devices for storage. Mobile devices in the fields can be approximated to millions. Individuals carry them to any place they go and may apply them to carry out various activities. Through the control of these equipments, we are in the position to come up with efficient community-centered sensing applications. For example, other than putting cameras on the sides of the roads or streets, we can come up with use of smart phones to collect such data. This is a good step towards the reduction of deployment cost spent on unique sensing infrastructure (Ganti et al.Page 34). Mobile devices used in mobile crowdsensing are efficient in the production of quality data in terms of accuracy and confidentiality. However, these features vary due to mobility and the level of energy and what the individual prefers. A major problem occurs during the identification of correct devices for the production of required data and the sensing of the usually carried by individuals putting the in a circle. These humans intelligence can be controlled to assist in suitable factors. These mobile devices are the applications in the collection of complex and data of high quality that may need complicated software and hardware. A good example is when human use the devices in the collection of data on parking which may require sending of text messages and pictures, as compared to ultrasound system for scanning which requires both unique hardware and algorithms that are sophisticated to make sure the data is reliable. Concerns are also coming up on the privacy of humans. They prefer of not making their location and private information that are sensitive known to anyone at some instances which are never inline with mobile crowdsensing goals. Participating individuals also acquire energy costs and monetary in the process of sensing and data communication. The owner of the devices may therefore fail to assist in the giving of such data. The success of the mobile crowdsensing therefore depends on the recruitment of human beings to carry out data sensing and this require appropriate incentives (Ganti et al.Page 35).The mobile devices also contain variety of sensors like GPS, microphone and camera. The applications accessibility to sensors and raw data extraction is controlled by OS. However considering the raw data conditions and application needs the reading of the sensors directly may not be compatible with applications direct utilization. Looking at the recent state of the MCS architecture, the current classic mobile crowdsensing application constitutes of two application particular components one placed on the device and the other one on cloud. The one on the device has its application as a sensor for compilation and transmission of data. Cloud is for sensor data examination to make the MCS application function. This is looks in terms of the architecture which has the applications placed in such away that they depend on their own. The applications however are facing various major challenges in the collection of data, distribution of resources and good use of energy. The architecture has been involved in forming barriers to MCS development through various ways. It is not easy to program the application. Developing new application will require the developer to look into the energy constraints, quality of data and privacy. The approach is also seen as an inefficient one. The independent carrying out of circulation and sensing activities without getting to know the negative results leads to low efficiency. There are high chances of duplication of sensing over various applications. The current architecture is also seen as non scalable. The number of applications contained by each device is limited. The data given by societal-scale sensing may also overcome networks and involved in the backending of the capability of the server (Ganti et al.Page 37). Some of the new developments coming up in decades include the smart phone capabilities to have electrocardiogram (ECG). This device measures the heart’s electrical activity (Ganti et al.Page 32). This involves the production of tiny electrical impulses that spreads through the muscle of heart causing the contraction n of the heart. These impulses are detected by the ECG machine. Incorporating this device in the smart phones would make it easier for an individual to the cause of symptoms like chest pain or palpitations done at any place. This will therefore not require that one must go to the hospital hence saving time. Good examples of these devices include Ithlete and Ha’ndy Sana mobile. Ithlete measures and predicts individuals training plan to strengthen his or her athlete performance as the health is maintained to maximum level. The device once put in the phone will measure the Heart Rate Variability (HRV) of an individual while he or she breath in a way that is relaxed and results given in a way of coded color stored for tracking. H’andy Sana targets people with heart problems. It allows the user to take an ECG and transfers it to the doctor from the phone. It requires the user to press the two fingers to the side of the phone which should be done for about thirty seconds and saved to the phone the transferred to the doctor. Another advance expected in the future is Intel’s EPIC which is used in the monitoring of air pollution. This device is incorporated with ozone, temperature, nitrogen and humidity sensors. It also constitute GPS/GPRS module hence involved in the collection of GPS data and uploading it to the servers in exact time. The device also has Bluetooth module. The other device coming in the future is for the detection of chemical that is poisonous, for example cell-all (Ganti et al.Page 32). In my conclusion the current state of mobile crowdsensing has shown to be crucial with its applications in the environment, infrastructure and social setting. Life has been made easier and faster as technology advances with people moving away from doing things manually. Daily routine activities can be monitored by use of mobile devices. The future also counts as devices for measuring heart rate and air pollution are brought into place. More discovering are being made as technology advances. However some challenges have shown to come about with the current state of mobile crowdsensing. The architecture has shown to be non scalable, low inefficiency and difficult in carrying out data programming. However solutions are still underway. REFERENCES Ganti, Raghu K., Fan Ye, and Hui Lei. "Mobile crowdsensing: current state and future challenges." Communications Magazine, IEEE 49.11 (2011): 32-39. Read More