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![Fig. 3. Actual Hardware Implementation [20].](profile/Sipiwe-Chihana/publication/327984762/figure/fig1/AS:676903253966878@1538397720878/Actual-Hardware-Implementation-20_Q320.jpg)
Zambia’s agricultural sector through Food Reserve Agency (FRA) while still underdeveloped faces many challenges that range from marketing, spoilage, infestations, and theft at site, spillage and storage among others. The methods used by FRA in their business processes are largely manual as there are no systems in place. In order to help curb these...
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... application makes use of the Arduino microcontroller, GSM and GPRS module as well as RFID. The hardware setup of this module is depicted in figure 7 below, and the working algorithm depicted in a flow chart in figure 8. ...
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p class="0papersubtitle">with advancement in technology, many sectors have seen growth and improvement in service delivery. Today, many areas such as health, transport and logistics, retailing among others have adopted the use of IoT. Agricultural sector has not been left out on the use of IoT. IoT is defined as a network of interconnected devices...
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... The digital pins are labelled from 0 to 13 and are used for digital input and output operations. connections of the hardware components [10]. Digital pins can be configured as either input or output and can be set high or low. ...
... Vacuumpacked goods are compatible with the system. A real-time intrusion and tracking system was suggested and built by Sipiwe Chihana et al. [9]. Suryawanshi VS et al. [10] proposed a system for food grain storage that timely monitors the temperature and humidity, which are the main two factors that can affect the quality of grain. ...
In daily life, vitamins fruits and vegetables play a very important role in human life. The farmer produces grains or vegetables in huge quantities. Due to lack of storage problem farmer suffers. It is necessary to store all these things in a special warehouse. Thus, improper storage of grains or fruits is essential to meet the increasing demands. Storage time and fruit quality are greatly influenced by storage environmental factors. Therefore, it is important for the fruit storage environment to perform multi-parameter monitoring and analyze the collected parameters and then regulate and control. The quality of grains and other perishable goods kept in a warehouse usually deteriorates due to lack of monitoring and proper maintenance of their required suitable conditions in such a large area. The proposed methodology deals with the storage of grains, fruits, etc., and to identify their temperature and humidity patterns so that they will not be degraded. Establishing the environment in relation to the nature of the crop so as to determine an optimum threshold with an appropriate pattern of monitoring and change. The main goal of this research article is to provide solutions to prevent rotting of grains and fruits in the storage area.
... People could serve as data sources or users with smart devices. For example, IoE technologies are beneficial to space optimization [36], environment monitoring [37], and process management [38] for smart warehousing. In addition, to timely capture and integrate the information on vehicles, cargoes and driver situations during transportation could effectively enhance the efficiency, ensure the quality and reduce the cost [39]. ...
The proliferation of the e-commerce market has posed challenges to staff safety, product quality, and operational efficiency, especially for cold chain logistics (CCL). Recently, the logistics of vaccine supply under the worldwide COVID-19 pandemic rearouses public attention and calls for innovative solutions to tackle the challenges remaining in CCL. Accordingly, this study proposes a cyber-physical platform framework applying the Internet of Everything (IoE) and Digital Twin (DT) technologies to promote information integration and provide smart services for different stakeholders in the CCL. In the platform, reams of data are generated, gathered, and leveraged to interconnect and digitalize physical things, people, and processes in cyberspace, paving the way for digital servitization. Deep learning techniques are used for accident identification and indoor localization based on Bluetooth Low Energy (BLE) to actualize real-time staff safety supervision in the cold warehouse. Both algorithms are designed to take advantage of the IoE infrastructure to achieve online self-adapting in response to surrounding evolutions. Besides, with the help of mobile and desktop applications, paperless operation for shipment, remote temperature and humidity (T&H) monitoring, anomaly detection and warning, and customer interaction are enabled. Thus, information traceability and visibility are highly fortified in this way. Finally, a real-life case study is conducted in a pharmaceutical distribution center to demonstrate the feasibility and practicality of the proposed platform and methods. The dedicated hardware and software are developed and deployed on site. As a result, the effectiveness of staff safety management, operational informatization, product quality assurance, and stakeholder loyalty maintenance shows a noticeable improvement. The insights and lessons harvested in this study may spark new ideas for researchers and inspire practitioners to meet similar needs in the industry.
... The Smart Industry has been challenging for researchers due to the variety, heterogeneity, and integration of the sub-domains 5 . Particularly the Industrial Internet of Things (IIoT) paradigm has stood out for its easy integration between industrial devices, allowing them to act in a synchronized and organized manner 6,7 . Furthermore, as Cyber-Physical Systems (CPS) allow the integration between the physical and digital environment, IIoT envision as part of Industry 4.0 or 4th industrial revolution 8,9,10 . ...
The IoT has made possible the development of increasingly driven services, like industrial IIoT services, that often deal with massive amounts of data. Meantime, as IIoT networks grow, the threats are even greater, and false data injection attacks (FDI) stand out as being one of the most aggressive. The majority of current solutions to handle this attack do not take into account the data validation, especially on the data clustering service. Aiming to advance on the issue, this work introduces CONFINIT, an intrusion detection system for mitigating FDI attacks on the data dissemination service performing in dense IIoT networks. CONFINIT combines watchdog surveillance and collaborative consensus strategies for assertively excluding various FDI attacks. The simulations showed that CONFINIT compared to DDFC increased by up to 35% - 40% the number of clusters without attackers in a gas pressure IIoT environment. CONFINIT achieved attack detection rates of 99%, accuracy of 90 and F1 score of 0.81 in multiple IIoT scenarios, with only up to 3.2% and 3.6% of false negatives and positives rates, respectively. Moreover, under two variants of FDI attacks, called Churn and Sensitive attacks, CONFINIT achieved detection rates of 100%, accuracy of 99 and F1 of 0.93 with less than 2% of false positives and negatives rates.
... The Smart Industry has been challenging for researchers due to the variety, heterogeneity, and integration of the sub-domains 5 . Particularly the Industrial Internet of Things (IIoT) paradigm has stood out for its easy integration between industrial devices, allowing them to act in a synchronized and organized manner 6,7 . Furthermore, as Cyber-Physical Systems (CPS) allow the integration between the physical and digital environment, IIoT envision as part of Industry 4.0 or 4th industrial revolution 8,9,10 . ...
The IoT has made possible the development of increasingly driven services, like industrial IIoT services, that often deal with massive amounts of data. Meantime, as IIoT networks grow, the threats are even greater, and false data injection attacks (FDI) stand out as being one of the most aggressive. The majority of current solutions to handle this attack do not take into account the data validation, especially on the data clustering service. Aiming to advance on the issue, this work introduces CONFINIT, an intrusion detection system for mitigating FDI attacks on the data dissemination service performing in dense IIoT networks. CONFINIT combines watchdog surveillance and collaborative consensus strategies for assertively excluding various FDI attacks. The simulations showed that CONFINIT compared to DDFC increased by up to 35%-40% the number of clusters without attackers in a gas pressure IIoT environment. CONFINIT achieved attack detection rates of 99%, accuracy of 90 and F1 score of 0.81 in multiple IIoT scenarios, with only up to 3.2% and 3.6% of false negatives and positives rates, respectively. Moreover, under two variants of FDI attacks, called Churn and Sensitive attacks, CONFINIT achieved detection rates of 100%, accuracy of 99 and F1 of 0.93 with less than 2% of false positives and negatives rates.
... Thinking about sensorial characteristics, the wrapped examples likewise kept up in general quality, particularly regarding natural product shading (glow), consistency, and taste. Chihana et al. (2018) investigated Zambia's agrarian area through Food Reserve Agency (FRA) while still immature faces numerous difficulties that range from showcasing, deterioration, invasions, and robbery at the site, spillage, and capacity among others. The techniques utilized by FRA in their business procedures are to a great extent manual as there are no frameworks set up. ...
In the development of the nation agriculture plays a significant role. IoT technology helps gather knowledge about environments such as wind, precipitation, temperature, and soil fertility. IoT allows farmers to get connected to their farm from anywhere at any time. Difficulty regarding agriculture has been always hampered; slow down the development of the country. These patterns benefit people in many respects, such as analysis using IoT and artificial intelligence, data sharing, and analytics in an unparalleled way. In this paper, we review IoT implementation in monitoring the environmental conditions of the crops and farms in various agriculture sectors. Additional IoT monitoring, control, and optimization functionality may be used to remotely monitor the control systems or actuators attached to the microcontrollers to ensure that the crop can react promptly as required. In this article, today’s climatic change scenario aims to establish a comprehensive vision of IoT implementation in the farming sector to improve agricultural production in the future, as well as to guarantee the constant supplier of food. We describe the advantages of applying IoT on livestock, weather surveillance, the agricultural warehouse, and the intelligent irrigation technique.
... Fig. 1 shows the conventional layered approach of the IoT-Fog-Cloud computing platform [1]. The revolutionary IoT technology consists of compact, reliable, and web-enabled wireless sensors that can relay pervasive information with maximum efficiency to remote locations [6]. ...
... Technically, the presented system comprises of a charging battery, microcontroller, a wireless module, MQTT Broker-supported mobile framework, and an Android-based food monitoring interface. In addition to these, works presented in [4,6,8], and [24] show efficient IoT-environments for tracking and analysis of food-industry based supply chains. Table 1 shows a comparative analysis with the presented model. ...
Fog-Cloud computing empowered Internet of Things (IoT) technology has conceptualized the ideology of Industry 4.0. Inspired by this, the food industry 4.0 presents a unique concept for determining food quality in real-time. Conspicuously, the current research provides an IoT-based smart framework for evaluating the food-quality parameters in restaurants and food outlets. IoT technology is primarily utilized to gather data that can explicitly affect food quality within a food serving environment. Such data is analyzed using the Bayesian Modeling Technique on the Fog-Cloud platform to derive a unanimous metric in terms of Probability of Food Grade (PoFG). Also, Food Grade Assessment Scale (FGAS) is quantified to assess real-time food-oriented parameters in the ambient environment of food-outlets and restaurants. Furthermore, a 2-player game-theoretic model is proposed for food quality-oriented decision services by monitoring officials and food managers. For evaluation purposes, the presented model is deployed over a challenging data set comprising of nearly 42,410 instances. The comparative simulations were carried out with state-of-the-art methodologies, which demonstrated the dominance of the presented model in terms of Data assessment efficacy, Statistical classification analysis, Decision-making efficiency, Reliability, and Stability.
... 5 IoT technology comprises small, robust, and internet-enabled wireless sensors that have the capability to transmit ubiquitous information to remote locations with maximal efficacy. 6 In the field of food technology, the trio-logical aspect of IoT-fog-cloud computing has been utilized to provide numerous applications related to food waste estimation, food quality assessment, and food-based cyber-physical systems. 7,8 According to a report by IFT in 2018, global agri-food technology investment was approximately 16.9 billion dollars, out of which 65% of money was spent on IoT-based smart solutions. ...
... 5. Estimating the reliability and stability of the proposed model for a large number of data segments. 6. In addition to these, a mathematical analysis of the proposed model is presented for depicting the overall accuracy. ...
Internet of Things (IoT) technology backed by fog‐cloud computing has conceptualized the notion of Industry 4.0. Motivated from this, smart restaurants presents a novel vision of provisioning effective food quality assessment based on game‐theoretic decision‐modeling techniques. This research presents an IoT‐inspired framework to analyze restaurants and food‐hubs for food quality perspective. Specifically, IoT technology is used to acquire ubiquitous data inside restaurant environment that can impact food quality directly and indirectly. This data is analyzed over the fog‐cloud computing platform to formulate a quantification measure in terms of probability of food quality using Bayesian modeling technique. In addition to this, food quality assurance index is estimated to present a unifying factor for food quality assessment over temporal scale. Finally, a three‐player game‐model is presented for food quality‐based decision making by the customers, restaurant managers, and monitoring officials. For validation purposes, the proposed model is deployed in four restaurants of Amritsar, India. The comparative analysis was performed with state‐of‐the‐art decision‐making modeling techniques, which showed the superiority of the presented technique in terms of temporal efficiency, statistical performance enhancement, correlation analysis, stability, and reliability. Moreover, a mathematical evaluation has been performed to depict the overall performance enhancement for the proposed decision‐making.
... In the IoT world, IoT applications can be different depending on the user's needs. Some examples of applications concern the monitoring of workouts through IoT devices [1], the control of the perimeter of houses/industrial environments [2], or sensors to measure the temperature and humidity of a monitored area [3]. The adoption of IoT in our lives introduces new opportunities for a large number of applications, where the primary aim is to improve the quality of human life. ...
The security of Internet of Things environments is a critical and trending topic, due to the nature of the networks and the sensitivity of the exchanged information. In this paper, we investigate the security of the Message Queue Telemetry Transport (MQTT) protocol, widely adopted in IoT infrastructures. We exploit two specific weaknesses of MQTT, identified during our research activities, allowing the client to configure the KeepAlive parameter and MQTT packets to execute an innovative cyber threat against the MQTT broker. In order to validate the exploitation of such vulnerabilities, we propose SlowTT, a novel "Slow" denial of service attack aimed at targeting MQTT through low-rate techniques, characterized by minimum attack bandwidth and computational power requirements. We validate SlowTT against real MQTT services, by considering both plaintext and encrypted communications and by comparing the effects of the attack when targeting different application daemons and protocol versions. Results show that SlowTT is extremely successful, and it can exploit the identified vulnerability to execute a denial of service against the IoT network by keeping the connection alive for a long time.
... The methods used by FRA in their business processes were largely manual as there were no systems in place. In order to help curb these problems, Chihana [21] proposed and developed novel methods that could be used to sense real-time warehouse intrusion and grain tracking within the FRA circulation. The IoT based prototype model made use of the APC220 transceiver, GSM, GPRS, RFID, PIR and cloud storage. ...
The University of Zambia like any public institution has a lot of infrastructure which require maintenance and management. There’s however uncertainty of the utility lines locations and their depths. This causes destruction of water pipes and sewer lines when undertaking new constructions or any excavations. The lack of accurate location of underground and un-updated lines makes maintenance, management and planning of the utilities very difficult. Therefore this study aimed to build a framework for Managing Sewer and Water Networks Using Sensor Networks at the University of Zambia. The Resident Engineer’s office only has some old scanned pdf sketches of both sewer and water networks. The field engineers locate most lines and other facilities using memory and experience. The methodology involved understating the existing operations of the Resident engineer’s office to ascertain the user needs. These needs formed the basis of the research, the development and design of the prototype of the Webbased Framework. Data Collection tools included Records (old maps) and Secondary Data (satellite images), Field Observations, Interviews and field Surveys. A presurvey (Reconnaissance Survey) was done to have an idea of the existing infrastructure and a more accurate survey was done using GPS GNSS equipment. The raw data was processed and GIS software was used to merge the collected datasets and the existing data. Georeferencing of existing maps and the satellite images was done using the GPS field data in ArcMap. New shapefiles were created from the point data from the survey and from digitising the existing scanned maps. New maps of the water and sewer networks (using the new shapefiles) and satellite imagery were created. A 15 digit coding system was created and was used to assign unique identification numbers and extra attribute information to the water and sewer network shapefiles. A QR code was generated for each node and the serial number recorded. Tagging was done using the QR code for each structure. All the shapefiles were loaded into a PostGreSQL spatial database and were used as input in the Web GIS application. The web application had some tools imbedded in it including; query, measure, add point/vertex, zoom, view, search and identify. Using internet of things (IOT) technology, water level sensors were placed on some critical manholes to help with the monitoring of the sewerage network. The system can therefore be used for identification of any infrastructure by scanning the QR code and a map showing the structure is seen online by the field technicians. Monitoring of the sewer system can be done using the sensors and ultimately the framework will ease the management of the water and sewer systems at the University of Zambia.
