MITS5003 Wireless Networks And Communication

It is the unlicensed ISM frequency band which is incorporated in many sensor systems for remote use. It allows for implementation flexibility due to the abundance of commercially available RF devices in the given band. There are different wireless sensor network systems operating frequencies allocated for different countries. For instance, in Europe, 315MHz, 433MHz, and 868 MHz; in North America 915MHz is allocated and the 2.45GHz is allocated as the industrial scientific medical, ISM, band [1].

PART B

Channel capacity or minimum data rate required for:

• One sensing device to control center channel
• Control center to ISP channel

For a sensor to communicate or send data to the central node, there is a single link. The bit rate or channel capacity considering the channel noises,

It’s a metric that determines the maximum amount of traffic or signal that can move over a particular infrastructure channel. Assuming a noiseless channel,

PART C

In the two channel types, calculate the noise levels experienced

• Thermal noise
• Total noise experience

The ambient temperature at 20⁰C causes a noise power proportional to the bandwidth. The thermal noise with respect to the ambient temperature is given as,

But, Thermal noise is estimated to be 5% of the total noise experience. Therefore,

PART D

Computing the signal power while SNR =63 at the control center for sensor signals

The power is given as,

Bandwidth,

PART E

To calculate the free space path loss of signals sent from the sensor to the center node,

Assumption: center node is in the middle of the farm (1.5 km from any perimeter in the farm)

Assumption: Sensor is about 1km from the center node,

PART F

Required transmission signal strength if other impairments such as the attenuation and fading causes loss of 30% in signal power during propagation from sensor to the control center.

PART G

Functionalities for the cloud application to effectively use sensor data: focus on the agriculture sector and business.

Cloud computing allows users to store data in remote location provided by service providers such as IBM, Google, Apple.Inc etc. The storage locations are ubiquitous, remotely hosted, and depend on a utility computing model. The data stored in the cloud storage locations can be used to determine the pattern the animals take. The information could show which locations have better grazing matter. The cloud provides integrated, networked, and internet infrastructure for information access and proper data transportation [2]. The platform abstracts the complexity and details of the underlying infrastructure from users and applications by providing very simple graphical interface or API. It provides processing tools for statistical analysis decision making tools and data trend or pattern identification. It guarantees improved performance, reduced software costs, unlimited storage capacity, increased data reliability, universal document access, easier group collaboration, and device independence [3].

PART H

IoT platforms in the implementation of WSN.

The IoT provides a global network of interconnected objects which are outfitted with sensors, actuators, and RFID devices. The wireless sensor network can help by enabling a level of standardization. The IoT equipment directly connects to the cloud hence there would be a swifter transmission of data to the cloud using inbuilt antennae. The systems are able to communicate and minimize noise level to very minimal levels. The implementation of IoT enables a range of items to be sensed, tracked and manipulated through IoT [4]-[6]. It is implemented in applications that desire real-time control with high reliability and that are mandatory while other applications employ a quasi-offline method over time scales in terms of hours to years.

References

• ANG, R.J., TAN, Y.K. and PANDA, S.K. Energy harvesting for autonomous wind sensor in remote area. 33rd Annual IEEE Conference of Industrial Electronics Society (IECON’07), Taipei, Taiwan, 2007.
• ASHTON, K. That ‘Internet of Things’ Thing. In the real world, things matter more than ideas. RFID Journal, 22 June 2009. Available from: https://www.r? djournal.com/articles/view?4986.
• BLILAT, A., BOUAYAD, A., CHAOUI, N. and EL GHAZI, M. Wireless sensor network: Security challenges. Network Security and Systems (JNS2), 2012 National Days of. IEEE, 2012, pp. 6872. Available from: https://novintarjome.com/wp-content/uploads/2014/05/Wireless-Sensor-Network.pdf
• CHONG, C.-Y. and KUMAR, S. P. Sensor networks: Evolution, opportunities, and challenges. Proceedings of the IEEE 91(8), 2003, pp. 1247-1256.
• IEC 62591, Industrial communication networks Wireless communication network and communication profitless WirelessHART™.
• TANG, L. and GUY C. Radio frequency energy harvesting in wireless sensor networks. International conference on communications and mobile computing, 2009, pp. 6446