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Iot Report

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Rajnish Raj

This document discusses the vision of a cloud-centric Internet of Things. It describes how ubiquitous sensing through wireless sensor networks can measure environmental indicators across many areas of life. As these sensing devices proliferate in communicating networks, they create the Internet of Things by seamlessly blending sensors and actuators with our environment. This generates enormous amounts of data that must be stored, processed, and presented seamlessly through cloud computing as a unifying framework. The document outlines key enabling technologies like RFID, wireless sensor networks, and addressing schemes. It also discusses applications, challenges, and the future direction of cloud-based IoT.

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A b s t r a c t Ubiquitous sensing enabled by Wireless Sensor Network (WSN) technologies cuts across many areas of modern day living. This offers the ability to measure, infer and understand environmental indicators, from delicate ecologies and natural resources to urban environments. The proliferation of these devices in a communicating–actuating network creates the Internet of Things (IoT), wherein sensors and actuators blend seamlessly with the environment around us, and the information is shared across platforms in order to develop a common operating picture (COP). Fueled by the recent adaptation of a variety of enabling wireless technologies such as RFID tags and embedded sensor and actuator nodes, the IoT has stepped out of its infancy and is the next revolutionary technology in transforming the Internet into a fully integrated Future Internet. As we move from www (static pages web) to web2 (social networking web) to web3 (ubiquitous computing web), the need for data-on-demand using sophisticated intuitive queries increases significantly. This paper presents a Cloud centric vision for worldwide implementation of Internet of Things. The key enabling technologies and application domains that are likely to drive IoT research in the near future are discussed. A Cloud implementation using Aneka, which is based on interaction of private and public Clouds is presented.
1. Introduction In the Internet of Things (IoT) paradigm, many of the objects that surround us will be on the network in one form or another. Radio Frequency IDentification (RFID) and sensor network technologies will rise to meet this new challenge, in which information and communication systems are invisibly embedded in the environment around us. This results in the generation of enormous amounts of data which have to be stored, processed and presented in a seamless, efficient, and easily interpretable form. This model will consist of services that are commodities and delivered in a manner similar to traditional commodities. Cloud computing can provide the virtual infrastructure for such utility computing which integrates monitoring devices, storage devices, analytics tools, visualization platforms and client delivery. The cost based model that Cloud computing offers will enable end-to-end service provisioning for businesses and users to access applications on demand from anywhere.
2. Definitions and elements. 2.1. Definitions :- Internet of Things can be realized in three paradigms—internet-oriented (middleware), things oriented (sensors) and semantic-oriented (knowledge). Although this type of delineation is required due to the interdisciplinary nature of the subject, the usefulness of IoT can be unleashed only in an application domain where the three paradigms intersect. Or Interconnection of sensing and actuating devices providing the ability to share information across platforms through a unified framework, developing a common operating picture for enabling innovative applications. This is achieved by seamless ubiquitous sensing, data analytics and information representation with Cloud computing as the unifying framework.
2.2. IoT elements There are three IoT components which enable seamless ubicomp: (a) Hardware—made up of sensors, actuators and embedded communication hardware (b) Middleware—on demand storage and computing tools for data analytics and (c) Presentation—novel easy to understand visualization and interpretation tools which can be widely accessed on different platforms and which can be designed for different applications. In this section, we discuss a few enabling technologies in these categories which will make up the three components stated above.
Continue... 2.2.1. Radio Frequency Identification (RFID):- RFID technology is a major breakthrough in the embedded communication paradigm which enables design of microchips for wireless data communication. They help in the automatic identification of anything they are attached to acting as an electronic barcode - 2.2.2. Wireless Sensor Networks (WSN):- Recent technological advances in low power integrated circuits and wireless communications have made available efficient, low cost, low power miniature devices for use in remote sensing applications. Sensor data are shared among sensor nodes and sent to a distributed or centralized system for analytics. 2.2.3. Addressing scheme:- IPv6 huge increase in address space is an important factor in the development of the Internet of Things. IPv6 would be able to communicate with devices attached to virtually all human-made objects because of the extremely large address space of the IPv6 protocol. This system would therefore be able to scale to the large numbers of objects envisaged.
Continue.... 2.2.4. Data storage and analytics:- One of the most important outcomes of this emerging field is the creation of an unprecedented amount of data. Storage, ownership and expiry of the data become critical issues. The data have to be stored and used intelligently for smart monitoring and actuation. It is important to develop artificial intelligence algorithms which could be centralized or distributed based on the need.
3. Applications 3.1. Personal and home:- An extension of the personal body area network is creating a home monitoring system for elderly care, which allows the doctor to monitor patients and the elderly in their homes thereby reducing hospitalization costs through early intervention and treatment and many more. 3.2. Enterprize:- We refer to the ‘Network of Things’ within a work environment as an enterprize based application. Information collected from such networks are used only by the owners and the data may be released selectively. Environmental monitoring is the first common application which is implemented to keep track of the number of occupants and manage the utilities within the building (e.g., HVAC, lighting) and many more. 3.3. Utilities:- for monitoring critical utilities and efficient resource management. The backbone network used can vary between cellular, Wi-Fi and satellite communication. Smart grid and smart metering is another potential IoT application. Water network monitoring and quality assurance of drinking water is another critical application and many more.
4. Cloud centric Internet of Things Smart objects will be endowed with sensors that will feed data back to cloud platforms for analysis. With so much data flowing in from potentially millions of different nodes, the diversity and precision of the knowledge we have about the world will explode. The cloud is the only technology suitable for filtering, analyzing, storing, and accessing that information in useful ways.
5. Open challenges and future directions 5.1. Architecture:- Most of the works relating to IoT architecture have been from the wireless sensor networks perspective. European Union projects of SENSEI and Internet of Things- Architecture (IoT-A) have been addressing the challenges particularly from theWSN perspective and have been very successful in defining the architecture for different applications. 5.2. Energy efficient sensing:- Efficient heterogeneous sensing of the urban environment needs to simultaneously meet competing demands of multiple sensing modalities. This has implications on network traffic, data for data collection and modelling that effectively exploits spatial storage, and energy utilization. Importantly, this encompasses both fixed and mobile sensing infrastructure as well as continuous and random sampling. A generalized framework is required and temporal characteristics of the data, both in the sensing domain as well as the associated transform domains .
Continue… 5.3. Secure reprogrammable networks and privacy:- Security will be a major concern wherever networks are deployed at large scale. There can be many ways the system could be attacked—disabling the network availability; pushing erroneous data into the network; accessing personal information; etc. The three physical components of IoT—RFID, WSN and cloud are vulnerable to such attacks. Security is critical to any network and the first line of defense against data corruption is cryptography. 5.4. Quality of service:- Heterogeneous networks are (by default) multi- service; providing more than one distinct application or service. This implies not only multiple traffic types within the network, but also the ability of a single network to support all applications without QoS compromise. each with its own application QoS needs is required [58]. It is not easy to provide QoS guarantees in wireless networks.
Continue…. 5.5. Data mining:- Extracting useful information from a complex sensing environment at different spatial and temporal resolutions is a challenging research problem in artificial intelligence. Current state-of-the-art methods use shallow learning methods where pre-defined events and data anomalies are extracted using supervised and unsupervised learning [66]. The next level of learning involves inferring local activities by using temporal information of events extracted from shallow learning. 5.6. Cloud computing:- Integrated IoT and Cloud computing applications enabling the creation of smart environments such as Smart Cities need to be able to :- (a) combine services offered by multiple stakeholders and (b) scale to support a large number of users in a reliable and decentralized manner. They need to be able operate in both wired and wireless network environments and deal with constraints such as access devices or data sources with limited power and unreliable connectivity.

More Related Content

Iot Report

  • 1. A b s t r a c t Ubiquitous sensing enabled by Wireless Sensor Network (WSN) technologies cuts across many areas of modern day living. This offers the ability to measure, infer and understand environmental indicators, from delicate ecologies and natural resources to urban environments. The proliferation of these devices in a communicating–actuating network creates the Internet of Things (IoT), wherein sensors and actuators blend seamlessly with the environment around us, and the information is shared across platforms in order to develop a common operating picture (COP). Fueled by the recent adaptation of a variety of enabling wireless technologies such as RFID tags and embedded sensor and actuator nodes, the IoT has stepped out of its infancy and is the next revolutionary technology in transforming the Internet into a fully integrated Future Internet. As we move from www (static pages web) to web2 (social networking web) to web3 (ubiquitous computing web), the need for data-on-demand using sophisticated intuitive queries increases significantly. This paper presents a Cloud centric vision for worldwide implementation of Internet of Things. The key enabling technologies and application domains that are likely to drive IoT research in the near future are discussed. A Cloud implementation using Aneka, which is based on interaction of private and public Clouds is presented.
  • 2. 1. Introduction In the Internet of Things (IoT) paradigm, many of the objects that surround us will be on the network in one form or another. Radio Frequency IDentification (RFID) and sensor network technologies will rise to meet this new challenge, in which information and communication systems are invisibly embedded in the environment around us. This results in the generation of enormous amounts of data which have to be stored, processed and presented in a seamless, efficient, and easily interpretable form. This model will consist of services that are commodities and delivered in a manner similar to traditional commodities. Cloud computing can provide the virtual infrastructure for such utility computing which integrates monitoring devices, storage devices, analytics tools, visualization platforms and client delivery. The cost based model that Cloud computing offers will enable end-to-end service provisioning for businesses and users to access applications on demand from anywhere.
  • 3. 2. Definitions and elements. 2.1. Definitions :- Internet of Things can be realized in three paradigms—internet-oriented (middleware), things oriented (sensors) and semantic-oriented (knowledge). Although this type of delineation is required due to the interdisciplinary nature of the subject, the usefulness of IoT can be unleashed only in an application domain where the three paradigms intersect. Or Interconnection of sensing and actuating devices providing the ability to share information across platforms through a unified framework, developing a common operating picture for enabling innovative applications. This is achieved by seamless ubiquitous sensing, data analytics and information representation with Cloud computing as the unifying framework.
  • 4. 2.2. IoT elements There are three IoT components which enable seamless ubicomp: (a) Hardware—made up of sensors, actuators and embedded communication hardware (b) Middleware—on demand storage and computing tools for data analytics and (c) Presentation—novel easy to understand visualization and interpretation tools which can be widely accessed on different platforms and which can be designed for different applications. In this section, we discuss a few enabling technologies in these categories which will make up the three components stated above.
  • 5. Continue... 2.2.1. Radio Frequency Identification (RFID):- RFID technology is a major breakthrough in the embedded communication paradigm which enables design of microchips for wireless data communication. They help in the automatic identification of anything they are attached to acting as an electronic barcode - 2.2.2. Wireless Sensor Networks (WSN):- Recent technological advances in low power integrated circuits and wireless communications have made available efficient, low cost, low power miniature devices for use in remote sensing applications. Sensor data are shared among sensor nodes and sent to a distributed or centralized system for analytics. 2.2.3. Addressing scheme:- IPv6 huge increase in address space is an important factor in the development of the Internet of Things. IPv6 would be able to communicate with devices attached to virtually all human-made objects because of the extremely large address space of the IPv6 protocol. This system would therefore be able to scale to the large numbers of objects envisaged.
  • 6. Continue.... 2.2.4. Data storage and analytics:- One of the most important outcomes of this emerging field is the creation of an unprecedented amount of data. Storage, ownership and expiry of the data become critical issues. The data have to be stored and used intelligently for smart monitoring and actuation. It is important to develop artificial intelligence algorithms which could be centralized or distributed based on the need.
  • 7. 3. Applications 3.1. Personal and home:- An extension of the personal body area network is creating a home monitoring system for elderly care, which allows the doctor to monitor patients and the elderly in their homes thereby reducing hospitalization costs through early intervention and treatment and many more. 3.2. Enterprize:- We refer to the ‘Network of Things’ within a work environment as an enterprize based application. Information collected from such networks are used only by the owners and the data may be released selectively. Environmental monitoring is the first common application which is implemented to keep track of the number of occupants and manage the utilities within the building (e.g., HVAC, lighting) and many more. 3.3. Utilities:- for monitoring critical utilities and efficient resource management. The backbone network used can vary between cellular, Wi-Fi and satellite communication. Smart grid and smart metering is another potential IoT application. Water network monitoring and quality assurance of drinking water is another critical application and many more.
  • 8. 4. Cloud centric Internet of Things Smart objects will be endowed with sensors that will feed data back to cloud platforms for analysis. With so much data flowing in from potentially millions of different nodes, the diversity and precision of the knowledge we have about the world will explode. The cloud is the only technology suitable for filtering, analyzing, storing, and accessing that information in useful ways.
  • 9. 5. Open challenges and future directions 5.1. Architecture:- Most of the works relating to IoT architecture have been from the wireless sensor networks perspective. European Union projects of SENSEI and Internet of Things- Architecture (IoT-A) have been addressing the challenges particularly from theWSN perspective and have been very successful in defining the architecture for different applications. 5.2. Energy efficient sensing:- Efficient heterogeneous sensing of the urban environment needs to simultaneously meet competing demands of multiple sensing modalities. This has implications on network traffic, data for data collection and modelling that effectively exploits spatial storage, and energy utilization. Importantly, this encompasses both fixed and mobile sensing infrastructure as well as continuous and random sampling. A generalized framework is required and temporal characteristics of the data, both in the sensing domain as well as the associated transform domains .
  • 10. Continue… 5.3. Secure reprogrammable networks and privacy:- Security will be a major concern wherever networks are deployed at large scale. There can be many ways the system could be attacked—disabling the network availability; pushing erroneous data into the network; accessing personal information; etc. The three physical components of IoT—RFID, WSN and cloud are vulnerable to such attacks. Security is critical to any network and the first line of defense against data corruption is cryptography. 5.4. Quality of service:- Heterogeneous networks are (by default) multi- service; providing more than one distinct application or service. This implies not only multiple traffic types within the network, but also the ability of a single network to support all applications without QoS compromise. each with its own application QoS needs is required [58]. It is not easy to provide QoS guarantees in wireless networks.
  • 11. Continue…. 5.5. Data mining:- Extracting useful information from a complex sensing environment at different spatial and temporal resolutions is a challenging research problem in artificial intelligence. Current state-of-the-art methods use shallow learning methods where pre-defined events and data anomalies are extracted using supervised and unsupervised learning [66]. The next level of learning involves inferring local activities by using temporal information of events extracted from shallow learning. 5.6. Cloud computing:- Integrated IoT and Cloud computing applications enabling the creation of smart environments such as Smart Cities need to be able to :- (a) combine services offered by multiple stakeholders and (b) scale to support a large number of users in a reliable and decentralized manner. They need to be able operate in both wired and wireless network environments and deal with constraints such as access devices or data sources with limited power and unreliable connectivity.