Figure 1: Ubiquitous network
II. UBIQUITOUS COMPUTING AND IOT
The word ‘ubiquitous’ has been originated from a Latin word ‘ubique’ meaning ‘everywhere’ . From IoT perspective we can see it as ‘anywhere’. Concept of IoT is based on three pillars viz. Anything, Anywhere and Anytime. So formally we may define IoT as it is a network of interconnected ‘things’ where anything can communicate with any other at any time.
The phrase IoT contains two words viz. internet and things. The word ‘internet’ implies the inter-connection of computing devices and ‘things’ refers to any uniquely identifiable device (with unique address). Computers, mobile phones, sensors, actuators etc everything can perform as a thing in IoT. The vision of IoT is to connect each and every object in this planet and thereby utilise the enormous capability of internetworked knowledge base during their operations. It’s not about how to add a particular service to a specific product, but to turn the signal / information generated by several sensors, devices, things and services to some meaningful knowledge about the environment and thereby to initiate some meaningful action. All the devices can be monitored and can be controlled overseas in real-time manner, if required. RFID tagging, sensor technology, networking, and nano-scale computing are taking major roles to enable IoT in reality.
III. ENABLING TECHNOLOGIES
To meet the vision of IoT properly we need to bring different technologies under one roof. Primarily five technologies are taking major roles to construct an IoT enabled service.
Ubiquitous ID: To connect an object in a network we must need a unique address. Statistics show that some trillions of things are coming under IoT in next few years . A big problem will arise due to the fact of allotting these enormous numbers of objects with unique addresses (ubiquitous id) using the present standard IPv4 (Internet Protocol version 4). This 32bit addressing can only generate billions of unique addresses. Solution is to use the IPv6 addressing (128 bit address) where more than 3.4 × 1038 unique addresses are available to identify a trillion objects each day for trillion years, and still there will be few available as unused .
RFID Tagging: The idea of Radio Frequency Identification (RFID) was first introduced to replace traditional barcode technology in 1973 to overcome some of its limitations. But slowly it has become a major pillar in IoT because of its automated and wireless nature. RFID is an automated data transmitting ‘thing’ that uses radio frequency to transfer data. RFID technology requires three elements viz. RFID tag, RFID reader, and middleware. There are mainly two types of RFID tags available e.g. Passive tags and Active tags . The RFID tag contains a very small chip that stores data about the object that is tagged and an antenna to transfer data. Passive tags do not have any inbuilt power supply. It uses electromagnetic induction from the reader to activate. The reader collects data from the tag and transfers them to the base station. Successful use of RFID can be seen in the shopping malls, manufacturing companies, smart homes, hospitals, libraries etc.
Transducers: Transducers are devices able to transform energy from one kind to another. Mainly two types of transducers are used in IoT technology, sensors and actuators. Sensors monitor the physical phenomenon of the system and actuators impose any action on the system. Sensor technology and wireless sensor network take leading role to enable IoT. Sensor sends data about the environment over the sensor network to the base station in real-time basis. Applications of sensors in IoT can be seen in weather forecasting, chemical plants, patient monitoring systems and so on.
Smart Technology: Intelligent software and hardware are used to make IoT a smart system. Machine automation technology is used to react with actuators accordingly with the environment. Today’s smart devices are clubbed to IoT systems to achieve its ultimate goal.
Nano-scale Computing and System Design: Nano technology acts as a shrink in IoT. The things are getting smaller and smaller to near microscopic elements in IoT. Integrated IC, NoC, SoC etc are taking major role to manufacture powerful integration of systems. Nano computing provides the opportunity of design complex, integrated, and microscopic devices to manufacture IoT enabled things.
IV. APPLICATIONS OF IOT
There are countless applications of IoT enabled technologies . Few of them are discussed here.
Health Care: A revolution in the medical science can be achieved with the help of IoT technology. A doctor can receive continuous information of patients’ physiological functions from the patient monitoring system in real-time basis and can assist the local doctors or control the local actuators in emergency situations from overseas.
Weather Forecasting: Continuous environmental information can be gathered continuously over the IoT network from the weather detecting sensors and can be forecasted to the citizens all the time.
Traffic Management: Intelligent traffic control system can be achieved from real-time traffic monitoring system.
Crowd Management: Emergency situations due to crowd can be handled from the crowd flow monitoring systems in stadiums, theatres, or railway stations.
Security and Surveillance: There are revolutionary applications of IoT in security and surveillance system. The security systems of our home and office can be under surveillance from anywhere over the network using IoT enabled devices.
V. CHALLENGES AND RESEARCH OPPORTUNITIES IN IOT
IoT is a big concept in communication centric computing perspective. And big ideas always have big challenges. Countless technologies need to be clubbed to implement the actual aim where all of them come with different technological background. To merge all those technologies we need to face various challenges. The spectrum of research required to achieve IoT at the scale envisioned above requires significant research along many directions. Some are discussed below.
Heterogeneous set of Things: An IoT enabled system runs with several heterogeneous devices those are different to each other in terms of communication protocol, data format, data collection, data storage capability etc. This is a challenging task to develop communication protocols supported by all devices. Standard data format is required to enable machine to machine (M2M) communication more efficiently.
Energy: Most of the devices in IoT are wireless in nature and live in remote places (e.g. environment monitoring sensors) where energy is the most vital issue. We need ultimate energy efficient algorithms and hardware.
Security: Unlike any online system, security is one of the most important issues. This issue becomes more challenging In an IoT when we are using the network ubiquitously. We require specific data isolation techniques to provide proper privilege to the end users according to their authority. Data encryption algorithms need to be much stronger. Most importantly, it should be energy efficient so that they could be used in very low power, low energy devices.
Privacy: The ubiquity and interactions involved in IoT can provide many conveniences and useful services for individuals, but also create many opportunities to violate privacy. To solve the privacy problem created by IoT applications of the future, the privacy policies for each (system) domain must be specified. Once specified either the individual IoT application or the IoT infrastructure (e.g., the utility capability) must enforce privacy. Consequently, the IoT paradigm must be able to express users’ requests for data access and the policies such that the requests can be evaluated against the policies in order to decide if they should be granted or denied. A new language is required to express privacy policies.
Intelligence: Machine to machine (M2M) communication has high priority in IoT because machine automation must be improved to minimise delay, traffic, and immediate action. Smart technologies need to be more intelligent to enable automated systems.
Communication Protocol: The heterogeneous nature of IoT enabled services meet an unavoidable problem with communication protocols . Each types of device use separate protocol in terms of data communication. Standard communication protocol needs to be developed for successfully implement IoT services.
Real-Time Solution: It will be really tough to implement the ‘Anytime’ concept of IoT in reality. The real-time systems need to be implemented in grass root level of the IoT things to react prominently at anytime. The complexity of the existing real-time systems must be minimised, so that they could be used in nano-scopic devices.
Creating knowledge and Big Data: In an IoT world there exist a vast amount of raw data being continuously collected. It can be expected that a very large number of real-time sensor data streams exist as it is common for a given stream of data to be used in many different ways for many different inference purposes. Here, the data provenance and how it was processed must be known, and privacy and security must be applied too. When the data is big, challenge becomes bigger. Data mining techniques are expected to provide the creation of important knowledge from all this data. In IoT system huge and huge amount of data needs to be managed in each second. It is said that 220 Exabytes of data will be stored in this year . The big-data concept must be implemented in IoT to manage this enormous amount of data. That’s why handling this big amount of data and creating knowledge from it is a major research problem for IoT.
Humans in the loop: As IoT applications demand more sophistication, many of these new applications will intimately involve humans, i.e., humans and things will operate synergistically. Human in-the-loop systems offer exciting opportunities to a broad range of applications including energy management , health care , and automobile systems [16, 19]. For example, it is hypothesized that explicitly incorporating human-in-the-loop models can improve safety, and using these models home health care can improve medical conditions of the elder people and keep them safe. Although having humans in the loop has its advantages, but modelling human behaviours is extremely challenging due to the complex psychological and behavioural aspect of human beings. New research is necessary to raise human-in-the-loop control to a central principle in system design and to solve key challenges .
IoT has been gradually bringing a series of technological changes in our daily lives, which in turn helps to make our life simpler and more comfortable through various technologies and applications. There is innumerable usefulness of IoT applications in various domains including medical, manufacturing, industrial, transportation, education, governance, mining, habitat etc. In spite of abundant benefits IoT is facing several flaws in governance and implementation level. Key observations in the literature are as follows. Firstly, there is no standard definition worldwide till date. Second, universal standardizations are required in architectural level too. Third, as technologies vary from vendor-to-vendor, interoperability issues are to be addressed more seriously. Lastly, for better global governance, we need to build uniformly accepted global standard protocols with proper safety and security issues.
 “The Internet of Things”, ITU Internet Reports, November 2005.
 “Internet of Things in 2020”, INFSO D.4 Networked Enterprise & RFIDINFSO G.2 Micro & Nanosystems, in co-operation with the Working Group RFID of The ETP EPoSS, Version 1.1 – 27 May, 2008.
 K. Sakamura, “Computers everywhere: The future of ubiquitous computing and networks”, MIC Japan/ITU/UNU WSIS Thematic Meeting “Towards the realization of the ubiquitous network society”, Tokyo, Japan, 16-17 May 2005.
 R. Prasad, ed. Future Trends and Challenges for ICT Standardization, Vol. 3, River Publishers, 2010.
 C. Cosgrove-Sacks, “Open protocols for an open, interoperable Internet of Things”, ITU Workshop, Geneva, Switzerland, 18 February 2014.
 K. Montgomery, “Children’s Media Culture in a Big Data World.” Journal of Children and Media 9.2 (2015): 266-271.
 “Gartner Says 4.9 Billion Connected “Things” Will Be in Use in 2015”, Barcelona, Spain, November 11, 2014, Available: www.gartner.com/newsroom/id/290571
 “Gartner Says that the Internet Of Things Will Change Cybersecurity Forever”, Mumbai, India, 02 September 2015, Available: www.gartner.com/newsroom/id/3123018
 L. Atzori, A. Iera, G. Morabito, “The Internet of Things: a survey”, Computer Networks (54), 2010, 2787–2805.
 F. Razzak, “Spamming the Internet of Things: A Possibility and its probable Solution”, Procedia Computer Science (10), 2012, 658-665
 S. Madakam, R. Ramaswamy, S. Tripathi, “Internet of Things (IoT): A Literature Review”, Journal of Computer and Communications (3), 2015, 164-173
 J. Gubbi, R. Buyya, S. Marusic, M. Palaniswami, “Internet of Things (IoT): A vision, architectural elements, and future directions”, Future Generation Computer Systems (29), 2013, 1645–1660.
 J. A. Stankovic, “Research Directions for the Internet of Things”, JIOT, IEEE, 2014
 T. Heer, O. Garcia-Morchony, R. Hummen, S. Loong Keohy, S. S. Kumary, and K. Wehrle, “Security Challenges in the IP-based Internet of Things”, COMSYS Group, RWTH Aachen University, Germany and Philips Research, the Netherlands.
 S. Munir, J. Stankovic, C. Liang, and S. Lin, “New Cyber Physical System Challenges for Human-in-the-Loop Control”, 8th International Workshop on Feedback Computing, June 2013.
 G. Burnham, J. Seo G. Bekey, A. “Identification of Human Driver Models in Car Following”, IEEE Transactions on Automatic Control 19, 6, 1974, pp. 911–915.
 M. Kay, E. Choe, J. Shepherd, B. Greenstein, N. Watson, S. Consolvo, and J. Kientz, “Lullaby: a Capture & Access System for Understanding the Sleep Environment”, UbiComp, 2012.
 J. Lu, T. Sookoor, V. Srinivasan, G. Gao, B. Holben J. Stankovic, E. Field, and K. Whitehouse, “The Smart Thermostat: Using Occupancy Sensors to Save Energy in Homes”, ACM SenSys, 2010.
 A Liu, and D. Salvucci, “Modeling and Prediction of Human Driver Behavior”, Intl. Conference on HCI, 2001.