Recent Advancements in ICT Infrastructure and Applications

Table of Contents

1. Frontmatter

2. Chapter 1. Introduction

   Manish Chaturvedi, Ramnarayan Yadav, Pankesh Patel

   Abstract

   The ubiquitous availability of the Internet and the advancements in communication, computing, and storage technologies have enabled a large number of Information and Communication Technology (ICT) applications. In this chapter, a few use cases of ICT applications are presented and the common framework of ICT applications is proposed. The framework consists of the building blocks/architectural components that are found in the majority of ICT applications. In particular, the framework includes the sensors and controllers, communication protocols, computation models, data processing and aggregation (intelligence layer), and security protocols. We describe all these building blocks in detail along with the technologies/solutions used in practice.

3. Chapter 2. Sensing 101

   Daniel J. de Carvalho, Victor W. C. de Medeiros, Glauco E. Gonçalves

   Abstract

   Today decision-making in all fields demands more and more environmental data, enabling estimates improvement, fine-control of manufacturing processes, and aggregation of more value to services. Scientific research currently also depends on accurate data for testing new hypotheses and discovering new phenomena. In other words, all these fields require a complete infrastructure for automatically sensing, storing, and transmitting data. State-of-the-art Information and Communications Technology (ICT) offers an array of options for environment sensing, from high-resolution sensors to low-cost alternatives. The main objective of this chapter is to introduce the reader to the field of physical world sensing through sensors and dataloggers, which are the cornerstones of current ICT applications. We provide a big picture of the area, presenting: basic concepts on sensing and embedded systems, aspects of sensors technologies and features, the wide range of interfaces that compose current dataloggers, and finally, we end the chapter discussing future directions in the field.

4. Chapter 3. FPGA-Based Error Correction in MEMS Sensors: Case Study of Respiration Monitoring System

   Idir Mellal, Youcef Fouzar, Laghrouche Mourad, Jumana Boussey

   Abstract

   Microelectromechanical System (MEMS) sensors are an essential branch of the microelectronic industry. They have been ubiquitously used in all live domains and applications, starting from general use with low precision and fewer constraints to high accuracy and harshest environments such as health and space applications. Thus, researchers have been investigating MEMS sensors in different aspects. One of the hottest aspects is related to the study and analysis of the measurement error in order to correct it. This work investigated and analyzed the sources and origins of different MEMS sensor errors and classified them into different categories. Moreover, various methods used in literature to correct the introduced errors and compensate the output drift have been explored. A practical example has been presented with a MEMS sensors applied to monitor human respiration activity. We designed a spirometry system to assess the respiration activity with a MEMS flow sensor and a 3D accelerometer placed on the chest. We modeled the output drift and proposed a compensation model based on Artificial Neural Network (ANN). Then we implemented the system on a Field Programmable Gate Array (FPGA) board. Different tests and measurements have been carried out. Therefore, different types of MEMS sensor errors have been presented and classified into random and deterministic errors. Furthermore, various parameters intervening at different stages and under different time/space constraints have been discussed. Moreover, the solutions used in the literature to correct the MEMS sensor outputs have been presented and compared. Finally, we presented an FPGA-based respiratory monitoring system using two MEMS sensors, a flow sensor, and an accelerometer. An ANN model has been used to compensate for the drift of the flow sensor. The performed tests on the nasal cannula showed a correlation between the analog and the digital outputs. This data is used to study the respiration rate. The accelerometer data collected on the chest has been used to detect chest movement and compute the tilt angle to understand the respiration activity.

5. Chapter 4. Computation Infrastructure: Data Offloading, Processing, and Privacy

   Yasasvitha Koganti, Ramnarayan Yadav, Sanjeet Kumar Nayak, Manish Chaturvedi

   Abstract

   This chapter elaborates the computation infrastructure, namely, cloud, fog, and edge computing. Various kinds of data offloading mechanisms and a general multi-layer computing framework addressing security aspects are presented. Presently, the smart Internet of Things (IoT) devices offload the large data aggregation and processing as well as storage to different computing platforms such as edge, fog, and cloud. In this chapter, various computing paradigms including their benefits and limitations are discussed. This chapter also discusses about the total cost in terms of latency and energy required to complete a task on user devices as well as remotely (on edge or cloud). Further, various necessary security and privacy issues are discussed that needs to be considered for large deployment of computing infrastructure for real-time ICT applications such as healthcare application. Finally, the chapter provides challenges and future directions for research in these computing paradigms, including security and privacy issues.

6. Chapter 5. Fog Computing Infrastructure for Smart City Applications

   Manju Lata, Vikas Kumar

   Abstract

   Fog computing offers an integrated key in support of communications, data gathering, device management, services capabilities, storage, and analysis at the edge of the network. This allows the deployment of centrally managed infrastructure in an extremely distributed environment. The present work discusses the most significant applications of fog computing for smart city infrastructure. In the smart city environment running a lot of IoT-based services, computing infrastructure becomes the most important concern. Thousands of smart objects, vehicles, mobiles, and people interact with each other to provide innovative services; here the fog computing infrastructure can be very useful from the perspective of data and communication. The chapter focuses on three main aspects: (a) deployment of data and software in fog nodes (b) fog-based data management and analytics, and (c) 5G communication using the fog infrastructure. Working models in all the perspectives have been presented to illustrate these fog computing applications. Use-cases have been added from the successful implementations of smart city infrastructure. Further, the challenges and opportunities have been presented from the perspective of growing interest in smart cities.

7. Chapter 6. Distributed Storage Infrastructure: Foundations, Analytics, Tools, and Applications

   Yashwant Singh Patel, Pushkar Kumar, Ramnarayan Yadav, Rajiv Misra

   Abstract

   The rapidly shifting technology landscape has allowed organizations to acquire the benefits of streamlined processes and cost-efficient operations. However, the availability of data from sources such as social data, machine data, transactional data, and many more has become a game changer for businesses of all sizes. These large stores of data known as Big data is challenging for an organization to handle or process. To improve the IT operations and optimize the faster processing, enterprises have adopted cloud computing. The integrated model of Cloud and Big data is a powerful combination that can transform the IT operations of the organization. This chapter provides a systematic overview of distributed storage infrastructures and discusses the current state-of-the-art solutions for storage technologies using Big data and cloud models. This chapter investigates the foundations, tools, and open research challenges of storing data using distributed storage infrastructures.

8. Chapter 7. Stream Data Processing Systems with Progressive Quality Improvement

   Chaxiong Yukonhiatou, Tomoki Yoshihisa, Tomoya Kawakami, Yuuichi Teranishi, Shinji Shimojo

   Abstract

   One of the main applications of stream data processing systems is detecting objects in video data streams. In such stream data processing systems, each camera device sends its recorded video data to the remote processing computer for the detections in cases that the computational resources of the camera devices are insufficient for the detections. To improve the performances of the stream processing systems for object detections, most methods reduce the communication traffic between the cameras and the processing computers. Although object detection processes do not always require the predetermined original data quality, the processing computers of conventional systems always receive original quality data. By considering the necessity of original quality data, we can reduce redundant communication traffic in some situations and can improve the performance indexes of the stream data processing systems. Hence, in this book chapter, we explain a Progressive Quality Improvement (PQI) approach to further improve the performances. In the PQI approach, for only the case that the data for higher qualities are needed, the processing computer progressively collects them from the data sources. Moreover, we implement a video surveillance system with the approach.

9. Chapter 8. Explainable AI for ICT: System and Software Architecture

   Devam Dave, Het Naik, Smiti Singhal, Rudresh Dwivedi, Pankesh Patel

   Abstract

   Artificial Intelligence (AI) has become a revolution in the ICT domain due to the swift progress of analytical techniques and the availability of structured/unstructured data. With the indispensable role of AI in different applications, there are growing concerns over the lack of transparency and explainability. In addition, potential bias may affect the predictions of a model. This is where Explainable Artificial Intelligence (XAI) comes into the picture. XAI increases the trust placed in an AI system by researchers, medical practitioners, and others. Thus, it leads to widespread deployment of AI in healthcare, agriculture, online mart, and many more. The aim is to enlighten practitioners on the understandability and interpretability of EAI systems using a variety of techniques available which can be very advantageous in the ICT domain. In this chapter, we present two different techniques leveraging EAI where a user has to make the right choices based on his requirements. The software architecture of the first techniques is based on a medical diagnosis model where we need to be confident enough to treat a patient as instructed by a black-box model. Another approach presents an online Mart where a reliable pricing method can be developed by ML models that can read through historical sales data. The objective here is to match buyers and sellers, to weigh animals, and to oversee their sale. However, when AI models suggest or recommend a decision, that in itself does not reveal too much (i.e., it acts as a black box). Hence, a model capable of explaining the different factors that impact the price point is essential for the needs of a user.

10. Chapter 9. Security Infrastructure for Cyber Attack Targeted Networks and Services

    Anmol Kumar, Gaurav Somani

    Abstract

    Cyber security covers various aspects of confidentiality, integrity, availability, and other related concepts for organizations and individuals. With the increase in web services, Internet enabled devices, and the amount of data generated, we see a huge growth in the number of cyber security incidents across the globe. Denial of service attacks, covert channel attacks, side-channel attacks, malware-driven attacks, and ransomware attacks are some of the most common cyber attack classes with a number of variants. These attacks may show various direct and indirect effects such as data loss, data leakage, data alteration, reputation loss, maintenance cost, malware spread, and service unavailability among others. There is number of levels in the overall target network or service hierarchy which need to have security deployments in the form of devices, software, filtering, and admission control mechanisms. In this chapter, we provide comprehensive detail on various modern security solutions across the overall spectrum of services. We categorize the modern security infrastructure into four categories which include network security, server security, cloud security, and device security infrastructures. We detail various primitives available in each of these categories in the state of the art and discuss their related security aspects.

11. Chapter 10. Case Studies: Cancelable Biometric-Based Secure Systems

    Rudresh Dwivedi, Somnath Dey

    Abstract

    Security theft and privacy invasion are two passive issues that still persist in the effective deployment of biometric-based authentication systems. Compromise of biometric data can potentially lead to serious security violation as the user’s biometric trait cannot be changed. In order to prevent the invasion of biometric templates, it is desired to morph the original biometric template through non-invertible or irreversible transformation function. This transformed template is referred to as cancelable template and can be replaced or reissued in case of compromise. The problem still persists if a protected multi-biometric template gets compromised. Objective of this book chapter is to address the mentioned concerns associated with template protection and investigate the template protection schemes for unimodal and multimodal biometric traits with large-scale biometric data so that the matching can be accomplished in transformed domain without compromising the verification performance. In this chapter, we present a discussion on efficient template protection scheme for unimodal and multimodal biometric authentication systems. Further, we also present the security models for few case studies on biometric systems, which attain performance improvement and provide adequate security to protect original biometric data.

12. Chapter 11. Cloud-based Remote Healthcare Delivery and Its Impact on Society: A Case Study

    Himadri Sekhar Ray, Sunanda Bose, Nandini Mukherjee

    Abstract

    Delivery of primary healthcare services to the doorstep of rural people in developing countries is a challenging task. It requires huge skilled workforce along with proper medical equipment for medical diagnosis and monitoring. In this chapter, we first present a survey of the cloud-based remote healthcare applications based on sensor, mobile and cloud technologies. Next, we describe a highly modular, easily re-configurable, touch-screen-based application with a user-friendly graphical interface for use in rural areas with no or minimal healthcare facilities. We have set up kiosks in the villages of West Bengal, India, where health assistants, with the help of our application, measure the patient’s vitals, collect symptoms by using a knowledge base and perform clinical examinations. The collected data are stored in a back-end cloud database server. Sitting at urban locations, doctors can check and examine patients’ clinical data, and prescribe medicines and tests. After 2 years of operation, a survey was conducted to understand the impact of using this mode of healthcare delivery. The chapter summarizes people’s perceptions and views in the second part of the chapter for further improvement and to strengthen the arena of the public health system. We also claim that such a system can become useful to handle a pandemic situation.

13. Backmatter