This chapter is focused on the basic concepts of sensors for the Internet of things (IoT). There is a wide variety of sensors, so to better manage them some type of classification will first be necessary. Then, the main characteristics of the sensors will be defined. Understanding these features will undoubtedly help in selecting the most suitable sensor for IoT applications. Finally, examples of commercial sensors particularly suitable for IoT applications are provided.

The article detailed the challenges in implementing a multisensor Android BLE application and a new methodology - SASC - was proposed to address these challenges. Benchmarking tests and free-living tests were conducted to validate the SASC implementation schemes. The benchmarking tests gave quantified results on metrics such as throughput, CPU loading on the smartphone and power consumption by the Android application for various number of sensors and varying connection intervals. The results of Android application throughput evaluation suggest that the maximum achievable throughput is ~20 kbps for a single sensor connection and ~70 kbps for a seven -sensor connection under SASC methodology. The results of the CPU loading and power consumption tests suggest that CPU loading and power consumption figures can be kept low by using a connection interval of 13.75 ms or greater. The proposed SASC methodology was also used in a real-life use case for gait data collection using SmartStep sensors, and a total of 19 days of human subject tests resulted in 100% data retrieval. These results suggest that the proposed methodology can serve as a foundation for applications that require managing multiple BLE connections in the world of IoT.

In a world when resources of living are scarce, urban people are suffering from a crisis of potable drinking water. The massive increase and concentration of human population in urban areas are liable for consumption of the vast majority of resources. Therefore it is highly pertinent to make cities greener and more sustainable. Advanced systems developed to improve and automate processes within a city will play a leading role in smart cities. From the intelligent design of buildings, which capture and harvest rainwater for future use, to smart control systems, which can monitor infrastructures autonomously, the possible improvements enabled by sensing technologies are of utmost importance. Internet of things (IoT)-enabled sensing and control poses numerous challenges, which are of a technological and social nature. The IoT solutions of smart water can help water utilities to coordinate analysis of supply and demand to provide smooth control actions across large numbers of distributed smart assets to monitor and deliver optimized performance to entire water production and distribution network. This ensures minimum water loss, assured water quality and quantity to every consumer. It is an excellent challenge in technology, and IoT-enabled smart assets will play a vital role towards the solution. The plugin Internet interface modules are developed to convert existing sensor and actuator system for secure and speedier communication of data to the central decision system either situated in the plant or in a cloud. All smart devices for water monitoring systems are M2M enabled and can share information directly or through the central system. The smart water solution technology is applicable for improvement of overall performance, quality and reliability of water and wastewater treatment and distribution system. The topic includes remote-based pipe monitoring and leak detection system to minimize nonrevenue water and to restore water supply in 24×7 manners with active operational management in damaged assets.

In this chapter, a wireless sensor network (WSN) application aimed for monitoring and warning about imminent landslides is presented. It consists of multiple complex measurement nodes (MNs) connected in a radio communication network spread over the area to be monitored. Each node is able to measure two types of parameters: relative soil layers displacement and pore water pressure, each of them mounted at different soil depths. The sensors devoted to measure the above parameters are of original conception and feature very good metrological qualities, especially in terms of displacement sensing sensitivity, which is as low as 1 mm per year. The measurement node structure can be tailored according to the underground layer structure and can include several displacement and pore water pressure sensors that are connected together in a wired local network structure with serial communication. The WSN is coordinated by a gateway, which has the role of general administration of the network resources, data collection and storage and information transmission to the cloud, from where a central server accesses and downloads the data. The whole structure of such a network is detailed in this chapter, starting with sensors description, continuing with the network architecture, communication protocols, data structure, alarms generation, data analysis, power management and ending with the user interface and some results obtained by in-field deploying of the network.

Internet of Things (IoT) is a very large domain, with a great variety of technologies and applications involved, spanning across a variety of business sectors. The goal of the present work is to model an IoT architecture for cargo ports. In this chapter the main objects/things and their roles in a cargo port, different sensors and instrumentation that was used or might be used for sensing and control in a cargo port and some examples of IoT technologies that might contribute for improving the safety of processes and the security of the ports are presented. The analysis of the data on information and communication technologies that were implemented or having potential application to cargo port logistic suggests that IoTs might contribute to increase the efficiency and the quality of services in cargo ports, the operational safety and the security of the ports, by increasing the accessibility and accuracy of relevant information.