Towards Autonomous IoT Logistics Objects

To improve the overall impact of the Internet of Things (IoT), intelligent capabilities must be developed at the edge of the IoT ‘Cloud.' ‘Smart' IoT objects must not only communicate with their environment, but also use embedded knowledge to interpret signals, and by making inferences augment their knowledge of their own state and that of their environment. Thus, intelligent IoT objects must improve their capabilities to make autonomous decisions without reliance to external computing infrastructure. In this chapter, we illustrate the concept of smart autonomous logistic objects with a proof of concept prototype built using an embedded version of the Prolog language, running on a Raspberry Pi credit-card-sized single-board computer to which an RFID reader is attached. The intelligent object is combining the RFID readings from its environment with embedded knowledge to infer new knowledge about its status. We test the system performance in a simulated environment consisting of logistics objects.

Innovation in Product Design

The IoT and 3D printing can become a potent combination when it comes to launching new business initiatives driven by hard-core data and analytics and not really based on human perceptions or limited survey data. Previous empirical research has shown that drivers of new product performance are a mix of strategic, development process, organizational, and market environmental factors. This chapter attempts (1) to understand how introduction of IoT sensors embedded in customer appliances or wearable's sending real time customer information coupled with rapid prototyping using remotely located 3D printers can help address design considerations for new products, and (2) to provide an overview of how using IoT data and 3D printers for new product development and prototyping as an early stage activity can be done without using human imagination of restricted market survey data.

User Acceptance of IoT Applications in Retail Industry

With the rapid advancements in the internet technology, many retailers are embracing internet of things technology to enhance customer experience and improve efficiency. Specifically, many customer-facing IoT technologies such as augmented reality, smart shopping carts, smart displays, and RFID tags are expected to change the way customers experience retailing shopping. Drawing on the technology acceptance model, trust perspective, task-technology fit, and organizational reputation perspective, this study examines the customer adoption of IoT applications in retail setting. Responses collected from 289 actual retail shoppers were analyzed using structural equation modeling. Results reveal that perceived usefulness, perceived ease of use, task-technology fit, retailer reputation, and initial trust are significant predictors of customer attitude and intentions to use IoT in retail stores. The study findings have key implications for academicians and retailers in improving customer acceptance and in delivering superior customer experience.

A Literature Review of the Emerging Field of IoT Using RFID and Its Applications in Supply Chain Management

The Internet of Things (IoT) envisions an ecosystem where smart and interconnected objects can sense surrounding changes, communicate with each other, process information and take active roles in decision making. Optimizing supply chain performance is a primary concern of manufacturing and logistics organizations. Radio Frequency Identification (RFID) is helping organizations to build automated and interconnected smart environment by object identification and tracking, motivating the first step towards an IoT-enabled world. This chapter attempts to understand extant literature studying applications of RFID in implementing the IoT in supply chain management. We categorize extant literature, firstly, based on research methodology and secondly, based on supply chain processes. We find that presently academic activity is around conceptualizing the usability of RFID in the IoT with limited analytical and empirical evidence. Supply chain processes such as demand planning, procurement, retail shelf space management and product returns are prospective areas for interesting future research.

Technopsychology of IoT Optimization in the Business World

There are at least two complementary levels in the Internet of Things. The first (back) end comes from the big data companies that mine and analyze every log of activities through every device that are attached to the second (front) end, i.e., the many aspects of our lives. However, what keeps this wheel of innovation going forward is actually the front end user. Technology, however improved and innovative, will not fulfill its full potential if users do not adopt and accept it as part of their lives. They must be willing to work with the technology - sold as way to ease and improve lives - for the machine to work and be meaningful. By then the big data companies can gather information about what users want and how they behave to grasp a better understanding and make better decisions about next technology improvement. Users' acceptance and decisions to appropriate shape how big data companies work and innovate. Acceptance and appropriation are the two of the most important areas to explore in the field of IoT optimization in the business world.

The Internet of Things

The Internet of Things (“IoT”), networks of connected machines and sensors with the ability to monitor and manage objects in the physical world electronically, has substantial economic potential. IoT technology has a wide range of applications, such as optimizing the performance of industrial operations and infrastructure systems; coordinating self-driving cars; managing the energy efficiency and security of homes and offices; and monitoring patients remotely. Drawing on a body of research by the McKinsey Global Institute (most notably, The Internet of Things: Mapping the value beyond the hype, June 2015), this chapter finds that the IoT could generate anywhere from $3.9 trillion to $11.1 trillion in annual economic impact by 2025. We arrive at these figures through a bottom-up quantification of economic surplus that examines multiple use cases clustered in nine types of settings where IoT technology has relevance. We also highlight some of the fundamental enablers that will be necessary for this value to be realized, including industrial adoption, interoperability standards, cybersecurity, and regulatory certainty regarding issues such as data sharing and liability. While these factors are not yet certain, we conclude that the current hype of IoT is somewhat justified. Indeed, if these issues are resolved quickly and fully, the eventual economic value may exceed current expectations.

The Internet of Things (IoT)

As the Internet of Things (IoT) opens up new business opportunities, firms are trying to understand the impacts of the IoT revolution on their supply chain. Despite the tremendous interest by supply chain managers to leverage the IoT, there are still a paucity of studies that integrate the management side of supply chain with the technical side of the IoT. This chapter attempts to fill the current gap in research. This chapter discusses capabilities of the IoT-based supply chain applications. Then, it presents a conceptual framework of the IoT applications essential for smart supply chain. Finally, this chapter discusses technical and managerial challenges faced by supply chain managers in implementing the IoT.

Computational Business Intelligence, Big Data, and Their Role in Business Decisions in the Age of the Internet of Things

The evolution of the big data and new techniques related to the processing and analysis of large databases is revolutionizing the management of companies in the age of the Internet of Things (IoT). In this chapter, we examine the possibilities of big data to improve the services offered by companies and the customer experience and increase the efficiency of these companies. Companies must accept the challenge of self-assessment and measure the barriers that threaten to prevent them from reaching to get the maximum potential derived from big data and analytics. The combination of big data and computational business intelligence will change completely processes, logistics and distribution strategies, the choice of marketing channels and any aspect of the production and marketing of products and services. A case of GE is presented to showcase the use of the IoT and big data. All companies, regardless of size or sector, will improve their business operations due to big data generated from the social media and IoT applications and its use in computational business intelligence.

The Human-IoT Ecosystem

IoT devices offer a cheap and powerful approach to identifying real world states and situations and acting on this real world environment to change these states and the environment. Augmenting real world things with IoT technology enables the capture of real world context to support decision making and actions in the real world via powerful smart objects in a human- IoT ecosystem. Increasingly we will have to understand the Human-IoT or smart device ecosystem interaction in order to optimise and integrate the design of human and IoT systems. This chapter explores the design and categorisation of IoT devices in terms of their functionality and capability to support context to add to human perception. It then proposes how we can model the context information of both IoT devices and humans in a way that may help progress Human-IoT Ecosystem design using situation theory.

Privacy in the Internet of Things

Internet of Things technology is rapidly gaining popularity, not only in industrial and commercial environments, but also in personal life by means of smart devices at home. The Internet of Things (IoT) spawn new businesses and make buildings, cities and transport smarter. The IoT allows for ubiquitous data collection or tracking, but these useful features are also examples of privacy threats that are already limiting the success of the IoT vision when not implemented correctly. Privacy should be protected in the device, in storage, during communication, and at processing. The privacy of users and their data protection have been identified as one of the important challenges that need to be addressed in the IoT. The chapter presents the IoT technology, the various applications, and privacy issues. Various other issues such as security and performance are also addressed.