internet of things

Wireless sensor networks (WSN)

-consist of spatially distributed sensor-equipped devices to monitor physical or environmental conditions -can cooperate with RFID systems to better track the status of things such as their location, temperature, and movements

RFID

Allows automatic identification and data capture using radio waves, a tag, and a reader.

Security challenge

As number and variety of connected devices introduced into IoT networks, the potential security threat escalates. IoT increases the potential attack surfaces for hackers and other cyber criminals

Cloud computing - IaaS+SaaS+data storage

Cloud computing - model for on-demand access to a shared pool of configurable resources (e.g., computers, networks, servers, storage, applications, services, software) Can be provisioned as Infrastructure as a Service (IaaS) or Software as a Service (SaaS). Many IoT applications require massive data storage, huge processing speed to enable real- time decision making, and high-speed broadband networks to stream data, audio, or video. Cloud computing provides an ideal back-end solution for handling huge data streams and processing them for the unprecedented number of IoT devices and humans in real time.

Challenges in IoT development

Data management challenge Data mining challenge Privacy challenge Security challenge Chaos challenge

Privacy challenge

IoT devices can provide data on IoT users' location and movements, health conditions, and purchasing preferences-—all of which can spark significant privacy concerns. Protecting privacy is often counter- productive to service providers in this scenario, as data generated by the IoT is key to improving the quality of people's lives and decreasing service providers' costs by streamlining operations.

IoT enterprise applications

Monitoring and control systems collect data on equipment performance, energy usage, and environmental conditions transportation and logistics applications monitor status of transported goods such as fruits, meats, dairy products Big data and business analytics Business analytics tools may be embedded into IoT devices wearable health monitoring sensors - remote monitoring -- real-time decision making can take place at the source of data Information sharing and collaboration occurs between people, between people and things, and between things In supply chain, information sharing and collaboration enhance situational awareness and avoid information delay and distortion. For example, if sensors are placed throughout a retail store where refrigeration is necessary, alerts can be sent to the store manager's mobile device whenever the refrigerators malfunction

IoT essential technologies

RFID Wireless sensor networks Middleware Cloud computing - IaaS+SaaS+data storage IoT applications

Middleware

Software layer between software applications to make it easier for software developers to perform communication and input/ output. Hides details of different technologies fundamental to free IoT developers from software services that are not directly relevant to the specific IoT application. Middleware gained popularity in the 1980s due to its major role in simplifying the integration of legacy technologies into new ones. Complex distributed infrastructure of the IoT with numerous heterogeneous devices requires simplifying the development of new applications and services, so the use of middleware is an ideal fit with IoT application development.

Chaos challenge

The evolution of IoT technologies (e.g., chips, sensors, wireless technologies) is in a hyper- accelerated innovation cycle that is much faster than the typical consumer product innovation cycle. competing standards, insufficient security, privacy issues, complex communications, and proliferating numbers of poorly tested devices. If not designed carefully, multi-purpose devices and collaborative applications can turn our lives into chaos. In an unconnected world, a small error or mistake does not bring down a system; however, in a hyper-connected world, an error in one part of a system can cause disorder throughout.

Data mining challenge

Traditional data mining techniques are not directly applicable to unstructured images and video data. there is a shortage of competent data analysts

How do real options evaluate IoT value? How do they differ from NPV?

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What is the Internet of Things (IoT)?

also called the Internet of Everything or the Industrial Internet new technology paradigm envisioned as global network of machines and devices capable of interacting with each other

Data management challenge

current architecture of the data center is not prepared to deal with the heterogeneous nature and sheer volume of personal and enterprise data (Gartner, 2014). Few enterprises would be able to invest in data storage sufficient to house all the IoT data collected from their networks. Must prioritize