Energy consumption -IoT

enrgyconsumption

The intelligent behavioral billing systems can help energy producers, distributors and consumers to be smarter in the use of energy saving costs while conserving vital energy resources.

Billing can be utilized by energy producer by allowing variable billing rates based on time, bundled packages, group rates, changes in consumption and other behavioral factors. In conjunction with smart wireless meter readers as IoT, the energy distributor can use behavioral billing by tracking the end consumer usage on a real time basis allowing billing to be performed with different rates depending on the time being consumed.

Affecting energy consumption of buildings considering different contexts, the effect of including data predictions and behavior patterns in the management of the building; the capability of the system for auto-assessment and auto-adjustment to changes in the context; and finally, the semantic perspective of technologies to translate data into a common language format considering related ontology.

The mobile crowd-based sensing techniques for gathering data from occupants’ devices, since this information will be able to complement the data obtained by the infrastructure-based system.

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Cloud Computing in Internet of Things

Cloud Computing in Internet of Things:

Cloud

Cloud computing can provide the virtual infrastructure for utility computing integrating applications, monitoring devices, storage devices, analytics tools, visualization platforms, and client delivery. The utility-based model that cloud computing offers will enable businesses and users to access applications on demand anytime, anyplace and anywhere.The growth of the Internet of Thing (IoT) and the rapid development of technologies create a widespread connection of “thing”. This will lead to the production of large amounts of data, which needs to be stores, processed and accessed. Cloud computing as a paradigm for big data storage and analytics. While the Internet of Thing is exciting on its own that the real innovation will come from combining it with cloud computing.
There are two systems in the cloud that will be used, which are to transform data to insight and drive productive, cost-effective actions from these insights.
The computer is connected with the Internet based on the service models which is Infrastructure-as-a-Service (IaaS), Platform-as-a-Service (PaaS), and Software-as-a-Service (SaaS) [2]. The cloud is the only technology suitable for filtering, analyzing, storing, and accessing the information.

The deployment of architectures and methodologies to strengthen the security and dependability of cloud computing for IoT.

Secure architecture and models for integration of cloud and IoT
Protocol design for secure communication between cloud and IoT
Cloud-assisted secure sensor data streaming
Threat and vulnerability modeling for cloud-assisted IoT
Trust establishment and management for cloud-assisted IoT
Data security, privacy, and reliability for cloud and IoT integration
Secure data management for integrated cloud and IoT
Risk/threat assessment and management for cloud-assisted IoT
Access control and identity management frameworks for cloud-assisted IoT
Authentication, authorization, auditing mechanisms for cloud-assisted IoT
Fault-tolerant and secure applications/frameworks for cloud-assisted IoT
Key management for integrated cloud and IoT
Innovative applications for cloud-assisted IoT

IoT-A Reference Model

IoT-A Reference Model

reference Iot

– Physical Devices and Controllers
The physical devices and controllers that might control multiple devices.
These are the “things” in the IoT, and they include a wide range of endpoint devices that send and receive information.

– Connectivity
Communications and connectivity, the objective of the IoT Reference Model is for communications and processing to be executed by existing networks.

– Computing
● Evaluation: Evaluating data for criteria as to whether it should be processed at a higher level
● Formatting: Reformatting data for consistent higher-level processing
● Expanding/decoding: Handling cryptic data with additional context (such as the origin)
● Distillation/reduction: Reducing and/or summarizing data to minimize the impact of data and traffic on the
network and higher-level processing systems
● Assessment: Determining whether data represents a threshold or alert; this could include redirecting data to additional destinations

– Data Accumulation
If data is of interest to higher levels: processing is the first level that is configured to serve the
specific needs of a higher level.
● If data must be persisted: Should data be kept on disk in a non-volatile state or accumulated in memory for short-term use?
● The type of storage needed: Does persistency require a file system, big data system, or relational database?
● If data is organized properly: Is the data appropriately organized for the required storage system?
● If data must be recombined or recomputed: Data might be combined, recomputed, or aggregated with previously stored information, some of which may have come from non-IoT sources.

– Data Abstraction
The data abstraction level must process many different things.
● Reconciling multiple data formats from different sources
● Assuring consistent semantics of data across sources
● Confirming that data is complete to the higher-level application
● Consolidating data into one place (with ETL, ELT, or data replication) or providing access to multiple data stores through data virtualization
● Protecting data with appropriate authentication and authorization
● Normalizing or denormalizing and indexing data to provide fast application access

– Application((Reporting, Analytics, Control)
Mission-critical business applications, such as generalized ERP or specialized industry solutions
● Mobile applications that handle simple interactions
● Business intelligence reports, where the application is the BI server
● Analytic applications that interpret data for business decisions
● System management/control center applications that control the IoT system itself and don’t act on the data produced by it.

– Collaboration and Processes(Involving people and business processes)
The IoT system, and the information it create, is of little value unless it yields action, which often requires people and processes.
Applications execute business logic to empower people. People use applications and associated data for their specific needs. Often, multiple people use the same application for a range of different purposes. So the objective is not the application—it is to empower people to do their work better. Applications give business people the right data, at the right time, so they can do the right thing.

Internet of Things—Architecture

Internet of Things—Architecture 

IoT Architecture

The basis for the IoT Reference Architecture structuring approach.

• Functional – Describes the system’s runtime functional elements and their responsibilities, interfaces , and primary interactions

• Information – Describes the way that the architecture stores, manipulates, manages, and distributes data and information.

• Deployment – Describes the environment into which the system will be deployed, including the dependencies the system has on its runtime environment

• Operational – Describes how the system will be operated, administered, and supported when it is running in it s production environment

Quality aspects of the IoT reference architecture are addressed through definitions of perspectives. The perspectives and their definition are provided in the following list:

• Security and privacy – Provides and analysis of the security threads in the functionality groups of the architecture and gives an explanation how security and privacy concerns should be addressed.

• Performance and scalability – Provides the ability of the system to handle a large number of devices, services and processes in an efficient way. Further more, the fluctuation of requests towards those has to be handled in a scalable way.

• Availability and resilience – The ability of the system to be fully or partly operational as and when required, and to effectively handle failures that could affect system availability

• Evolution and interoperability – The ability of the system to be flexible in the face of the inevitable change that all systems experience after deployment; the ability of two or more systems or components to exchange and use information
Field of application : Transportation/ Logistics

Logistics
Impacts:
In transport logistics, IoT improves not only material flow systems, but also global positioning and auto identification of freights. Additionally, it increases energy efficiency and decreases thus e nergy consumption. In conclusion, IoT is expected to bring profound chan ges to the global supply chain via intelligent cargo movement. This will be achieved by means of continuous process synchronisation of supply-chain information, and seamless real-time tracking and tracing of objects. It will provide the supply chain a transparent, visible and controllable nature, enabling intelligent communication between people and cargo.

Field of application : Smart home

smart home
Impacts:
Future smart homes will be conscious about what happens inside a building, mainly impacting three aspects: re source usage (water conservation and energy consumption), security, and comfort. The goal with all this is to achieve better levels of comfort while cutting overall expenditure. Moreover, smart homes also address security issues by means of complex security systems to detect theft, fire or unauthorized entries. The stakeholders involved in this scenario constitute a very heterogeneous group. There are different actors that will cooperate in the user’s home, such as Internet companies, device manufacturers, telecommunications operators, media-service providers, security companies, electric-utility companies, etc.

Field of application : Smart city

Smart City
Impacts:
While the term smart city is still a fuzzy concept, there is a general agreement that it is an urban area wh ich creates sustainable development and high quality of life. Giffinger et al .’s model elucidates the characteristics of a smart city, encompasing economy, people, governance, mobility, environment and living [Giffinger, 2007]. Outperforming in these key areas can be done through strong human or social capital and/or ICT infrastructure. For the latter, a first business analysis concludes that several sectors/industries will benefit from more digitalised and intelligent cities (examples for a city of 1 milli on people [Nicholson, 2010]): • Smart metering, 600.000 meters, US $ 120 million opportunity • Infrastructure for charging electric vehicles, 45.000 electric vehicles, US $ 225 million opportunity • Remote patient monitoring (diabetes), 70.000 people, US $ 14 million opportunity • Smart retail, 4.000 stores, US $ 200 million opportunity • Smart-bank branches, 3.200 PTMs, US $ 160 million opportunity

Field of application :Smart factory

smart factory
Impacts:
Companies will be able to track al l their products by means of RFID tags by means of a global supply chain; as a consequence, companies will reduce their OPEX and improve thei r productivity due to a tighter integration with ERP and other systems. Generally, IoT will provide automatic procedures that imply a drastic reduction in t he number of employees needed. Workers will be replaced by bar-code scanners, readers, sensors and actuators, and in the end by complex robots, as much efficient as a hu man. Without any doubt, these technologies will bring opportunities for white-collar workers and a big number of technicians will be necessary to program and repair these machines. This is synonymous to a transfer to maintenance jobs, but it also constitutes a new challenge for providing all blue-collar workers with an opportunity to move toward these types of jobs and to avoid unemployment.

Field of application : Retail

IOT retail
Impacts :
IoT realises both customer needs and business needs. Price comparison of a product; or looking for other products of the same quality at lower prices, or with shop promotions gives not only information to customers but also to shops and business. Having this informat ion in real time helps enterprises to improve their business and to satisfy customer needs. Obviously, big retail chai ns will take advantage of their dominant position in order to enforce the future IoT reta il market, as it happened with RFID adoption, which was enforced by WalMart in 2004 [Field, 2008]. Particularly, companies with controlling positions, such as WalMart, Carrefour, Metro AG, etc. are able to push the adoption of IoT technology due to their sizable market shares.

Field of Application : eHealth

IOT ehealth
Impacts :
Controlling and preventing is one of the main goals of future health care. Already today, people can have the possibility of being tracked and monitored by specialists even if both are not at the same place. Tracing peoples’ health history is another aspe ct that makes IoT-assisted eHealth very versatile. Business applications could offer the possibility of medical service not only to patients but also to specialists, who need information to proceed in their medical evaluation. In this domain, IoT makes human interaction much more efficient because it not only permits localization, but also tracking and monitoring of patient s. Providing information about the state of a patient makes the whole process more efficient, and also makes people much more satisfied. The most important stakeholders in th is scenario will be public and private hospitals and institutes such as, e.g ., the Institute of Applied eHealth at Edinburgh Napier University, which partook in the fi rst stakeholder session of IoT-A. It is worth mentioning that telecommunications operators are quite active in e-health (for instance, O2 UK).

Field of Application : Environment

IOT environment
Impacts :
From the aforementioned application we infe r that environment has many overlaps with other scenarios, such as smart home and smart city. The key issue in these scenarios is to detect mean s that help to save energy. We are basically referring to what is known as Smart Grid. Concerning this application area one needs to highlight initiatives that imply a more distributed energy production, since many houses have a solar panel today. As a vital part, smart metering is co nsidered as a pre-condition for enabling intelligent monitoring, control, and communication in grid applications. The use of IoT platforms in Smart Metering will provide the following benefits: • An efficient network of smart mete rs allows for faster outage detection and restoration of service. Such c apabilities redound to the benefit of customers • Provides customers wi th greater control over their energy or water consumption, providing them more choices for managing their bills. • IoT deployment of smart meters is expected to reduce the need to build power plants. Building power pl ants that are necessary only for occasional peak demand is very expensive. A more economical approach is to enable customers to reduce their demand through time-based rates or other incentive programs, or to use automatic recording of consumptions to turn off devices temporarily which are not in use. Finally, combining the analysis of supply and demand, energy enterprises will able to supply a more efficient dem and shaping. They will not just give incentives to consumers, but actually turning off devices that are not needed (like the freezer for 20 minutes). Also most of this needs to happen automatically.Here we again face a heterogeneous scenario, in which diverse stakeholders are involved. Main actors are of course energy utilities, but also public entities will be important players.

Elements of IoT

Elements of IoT

Wireless Sensor Networks (WSN)

wsn
Bridging between wireless sensor networks with traditional communication networks or Internet, IOT Gateway plays an important role in IOT applications, which facilitates the seamless integration of wireless sensor networks and mobile communication networks or Internet, and the management and control with wireless sensor networks. An IOT Gateway system based on Zigbee and GPRS protocols according to the typical IOT application scenarios and requirements from telecom operators, presented the data transmission between wireless sensor networks and mobile communication networks, protocol conversion of different sensor network protocols, and control functionalities for sensor networks, and finally gave an implementation of prototyping system and system validation.

Radio Frequency Identification (RFID)

rfid-basic-scheme
Radio frequency identification system (RFID) is an automatic technology and aids machines or computers to identify objects, record metadata or control individual target through radio waves. Connecting RFID reader to the terminal of Internet, the readers can identify, track and monitor the objects attached with tags globally, automatically, and in real time, if needed.

Addressing schemes

addressing
Naming schemes became parts of the solutions to the new challenges that lie ahead. Some are based on IP structure which is the cornerstone of today’s Internet. Some are brand new schemes part of future Internet architectures aiming to solve the tricky problems such as mobility and security for good.
– IP, the Domain Name System (DNS) and Uniform Resource Identifier (URI)
– IPv6 and IPv6 over Low power Wireless Personal Area Networks
– Content-Centric Network (CCN) and NDN
– Naming scheme of NDN
– MobilityFirst
– Global unique identifier (GUID) and Name Assignment Service (NAS)
– Naming schemes of NDN and MobilityFirst

Data, storage and analytics

Data
IOT ANALYTICS studies data generated by storage devices and alerts the enterprise or cloud service provider before a potential problem occurs, typically in areas such as proactive capacity planning, event analysis and licensing summary. It also enables storage providers to better understand how customers are configuring and using these storage systems, allowing storage providers to offer new features and capabilities that fit with customers’ evolving needs.
IoT analytics gives peace of mind to storage providers as well as their customers, by offering a proactive, automated approach to managing complex storage systems. In today’s big data-dominated environment, effective “big storage” is a big deal.

Visualization

Visualization
The Operations wants the ability to oversee his data center from any location on any device at any time without just seeing a bunch of pie charts and line graphs. He wants to see the representation and the geographic and physical representation of the equipment itself along with its most relevant set of information. He wants this information on his dashboard to upload quickly and respond so that it looks appropriate and legible whether he is on his desktop or on his cell phone. This allows him to easily evaluate his data center and make the quickest decisions according to the real-time and historic data trends and alarms displayed on his dashboard.

Security

security
Insecure Products & Insufficient Testing
One of the biggest concerns about smart buildings and smart cities is that the sensors in the equipment can be hacked and fed fake data — which could be used for all manner of mischief, like causing signal failures that shut down subways or allowing contaminants into the water supply

Huge, Complex Attack Surface
The trend is, the smarter the city, the more computer systems, the more integration between the systems, and the more open the access to the data collected by all those systems.

Lack of Oversight and Organization
“Who’s responsible when a smart city crashes?”

Shifting Politics, Shifting Budgets
“Cities are ultimately political beasts, with responsibilities to the populace,” and with that comes increased visibility, Conti says. That increased visibility can ultimately be either good or bad for security.

IoT – Components

components

Key components of an IoT software platform include:

Device connectivity software (hubs)
Emerging software vendors such as Octoblu (Citrix), Zonoff, Ayla, and Arrayent are enabling smart devices to connect with everything, regardless of protocol or API. Whether it’s a sensor, an appliance, a consumer electronics device, or industrial machinery, these “hub” software vendors allow users and systems to easily connect to and communicate to and from connected devices, typically bridging various wireless protocols such as ZigBee, Z-Wave, WiFi, and Bluetooth.

Big data store
With data growing so rapidly and the rise of unstructured data accounting for 90% of the data today, a big data store like Hadoop is imperative as part of an IoT platform. Splunk, SAP Hana, Amazon and Elastic MapReduce are all examples of tools in this category that can help store vast amount of data and enable rapid queries and aggregation against the data to support analytic requirements.

Analytics engine
This area covers the ability for users to mine data and analyze it to uncover interesting insights and run analytical reports. These insights can then be converted into revenue or cost saving opportunities for the organization that would otherwise have been difficult or impossible to find. Microstrategy, Pentaho and SAP BusinessObjects are all examples of modern analytics and business intelligence solutions.

Operational app services
This layer enables efficient development of apps that control devices, communicating with the device hub and integrating data from third-party services (push, SMS, email, amazon echo, etc.) and enterprise systems (SAP, Salesforce.com, Oracle, etc.), managing user identity and authentication, and securing data and workflow. Backend services (MBaaS), infrastructure, SDKs, and API solutions occupy this segment, represented by vendors like AnyPresence, Apigee, Mashery, and ThingWorx (PTC).

Developer ecosystem enablement tools
The most successful organizations in the IoT space will be those who can enable and foster a strong developer ecosystem, allowing partners, customers and developers to unlock the power of devices and data through APIs and SDKs. There are very few vendors in this emerging category, but AnyPresence offers some interesting capabilities with its App Launchpad solution, which is already in use at several large enterprises including MasterCard.