ELI: an IoT-aware big data pipeline with data curation and data quality.

The complexity of analysing data from IoT sensors requires the use of Big Data technologies, posing challenges such as data curation and data quality assessment. Not facing both aspects potentially can lead to erroneous decision-making (i.e., processing incorrectly treated data, introducing errors into processes, causing damage or increasing costs). This article presents ELI, an IoT-based Big Data pipeline for developing a data curation process and assessing the usability of data collected by IoT sensors in both offline and online scenarios. We propose the use of a pipeline that integrates data transformation and integration tools and a customisable decision model based on the Decision Model and Notation (DMN) to evaluate the data quality. Our study emphasises the importance of data curation and quality to integrate IoT information by identifying and discarding low-quality data that obstruct meaningful insights and introduce errors in decision making. We evaluated our approach in a smart farm scenario using agricultural humidity and temperature data collected from various types of sensors. Moreover, the proposed model exhibited consistent results in offline and online (stream data) scenarios. In addition, a performance evaluation has been developed, demonstrating its effectiveness. In summary, this article contributes to the development of a usable and effective IoT-based Big Data pipeline with data curation capabilities and assessing data usability in both online and offline scenarios. Additionally, it introduces customisable decision models for measuring data quality across multiple dimensions.

Homomorphic Asymmetric Encryption Applied to the Analysis of IoT Communications.

In this paper, we describe the use of homomorphic encryption techniques in order to not only ensure the data are transmitted in a confidential way, but also to use the encrypted data to provide the manager with statistics that allow them to detect the incorrect functioning of a sensor node or a group of sensors due to either malicious data injection, data transmission, or simply sensor damage (miscalibration, faulty sensor functioning). Obtaining these statistical values does not need decryption, so the process is sped up and can be developed in real time. Operating the data in this way ensures privacy and removes the need to maintain a shared key infrastructure between the sensor nodes and the manager nodes that are part of the blockchain infrastructure. In this work, we focus on operations with the sensor nodes that provide data that will be, later, treated as part of the business logic in the agribusiness sector (for example), hence the importance of having fast checking mechanisms in terms of data quality. The results obtained on conventional configurations of sensor nodes encourage the use of this technique in the aforementioned infrastructure.

Blockchain from the Perspective of Privacy and Anonymisation: A Systematic Literature Review.

The research presented aims to investigate the relationship between privacy and anonymisation in blockchain technologies on different fields of application. The study is carried out through a systematic literature review in different databases, obtaining in a first phase of selection 199 publications, of which 28 were selected for data extraction. The results obtained provide a strong relationship between privacy and anonymisation in most of the fields of application of blockchain, as well as a description of the techniques used for this purpose, such as Ring Signature, homomorphic encryption, k-anonymity or data obfuscation. Among the literature researched, some limitations and future lines of research on issues close to blockchain technology in the different fields of application can be detected. As conclusion, we extract the different degrees of application of privacy according to the mechanisms used and different techniques for the implementation of anonymisation, being one of the risks for privacy the traceability of the operations.

Distributed Key Management to Secure IoT Wireless Sensor Networks in Smart-Agro.

With the deepening of the research and development in the field of embedded devices, the paradigm of the Internet of things (IoT) is gaining momentum. Its technology's widespread applications increasing the number of connected devices constantly. IoT is built on sensor networks, which are enabling a new variety of solutions for applications in several fields (health, industry, defense, agrifood and agro sectors, etc.). Wireless communications are indispensable for taking full advantage of sensor networks but implies new requirements in the security and privacy of communications. Security in wireless sensor networks (WSNs) is a major challenge for extending IoT applications, in particular those related to the smart-agro. Moreover, limitations on processing capabilities of sensor nodes, and power consumption have made the encryption techniques devised for conventional networks not feasible. In such scenario, symmetric-key ciphers are preferred for key management in WSN; key distribution is therefore an issue. In this work, we provide a concrete implementation of a novel scalable group distributed key management method and a protocol for securing communications in IoT systems used in the smart agro sector, based on elliptic curve cryptography, to ensure that information exchange between layers of the IoT framework is not affected by sensor faults or intentional attacks. In this sense, each sensor node executes an initial key agreement, which is done through every member's public information in just two rounds and uses some authenticating information that avoids external intrusions. Further rekeying operations require just a single message and provide backward and forward security.

DNA Sequencing Sensors: An Overview.

The first sequencing of a complete genome was published forty years ago by the double Nobel Prize in Chemistry winner Frederick Sanger. That corresponded to the small sized genome of a bacteriophage, but since then there have been many complex organisms whose DNA have been sequenced. This was possible thanks to continuous advances in the fields of biochemistry and molecular genetics, but also in other areas such as nanotechnology and computing. Nowadays, sequencing sensors based on genetic material have little to do with those used by Sanger. The emergence of mass sequencing sensors, or new generation sequencing (NGS) meant a quantitative leap both in the volume of genetic material that was able to be sequenced in each trial, as well as in the time per run and its cost. One can envisage that incoming technologies, already known as fourth generation sequencing, will continue to cheapen the trials by increasing DNA reading lengths in each run. All of this would be impossible without sensors and detection systems becoming smaller and more precise. This article provides a comprehensive overview on sensors for DNA sequencing developed within the last 40 years.

Microfluidic paper-based device for colorimetric determination of glucose based on a metal-organic framework acting as peroxidase mimetic.

This work presents a microfluidic paper-based analytical device (µPAD) for glucose determination using a supported metal-organic framework (MOF) acting as a peroxidase mimic. The catalytic action of glucose oxidase (GOx) on glucose causes the formation of H2O2, and the MOF causes the oxidation of 3,3',5,5'-tetramethylbenzidine (TMB) by H2O2 to form a blue-green product with an absorption peak at 650 nm in the detection zone. A digital camera and the iOS feature of a smartphone are used for the quantitation of glucose with the S coordinate of the HSV color space as the analytical parameter. Different factors such as the concentration of TMB, GOx and MOF, pH and buffer, sample volume, reaction time and reagent position in the µPAD were optimized. Under optimal conditions, the value for the S coordinate increases linearly up to 150 µmol·L-1 glucose concentrations, with a 2.5 µmol·L-1 detection limit. The µPAD remains stable for 21 days under conventional storage conditions. Such an enzyme mimetic-based assay to glucose determination using Fe-MIL-101 MOF implemented in a microfluidic paper-based device possesses advantages over enzyme-based assays in terms of costs, durability and stability compared to other existing glucose determination methods. The procedure was applied to the determination of glucose in (spiked) serum and urine. Graphical abstract Schematic representation of microfluidic paper-based analytical device using metal-organic framework as a peroxidase mimic for colorimetric glucose detection with digital camera or smartphone and iOS app readout.

Tetrazine-based chemistry for nitrite determination in a paper microfluidic device.

We present a new chemistry to determine nitrites implemented in a microfluidic paper-based analytical device (µPAD). The device is fabricated in cellulose paper with a sample reception area and three replicate detection areas with recognition chemistry immobilized by adsorption. The method involves the use of nitrite in an acid medium reaction to generate nitrous acid, which produces the oxidation of s-dihydrotetrazine: 1,2-dihydro-3,6-bis(3,5-dimethyl-1H-pyrazol-1-yl)-1,2,4,5-tetrazine (DHBPTz), which change the detection zone from colorless to pink. We used a digital camera and smartphone for the quantitative analysis of nitrite with the color coordinate S of the HSV color space as the analytical parameter. Parameters such as concentration and volume of s-dihydrotetrazine, pH, sample volume and reaction time were studied. The detection limit for this method is 1.30µM nitrite. To estimate the selectivity of the method an interference study of common ions in water samples was performed. The procedure was applied to natural water and compared with reference procedures.