Blockchain and e-government innovation: Automation of public information processes

Blockchain technology is a ledger system that is popularly known as the backbone of the Bitcoin cryptocur-rency. Since its conception, the potential beneficial applications of blockchain in other digital sectors have been lauded in the literature, and related challenges have been disputed. In this study, the literature is reviewed for frameworks and use cases that fully realize the applicability of blockchain beyond financial applications and cryptocurrencies. A network analysis of the literature was performed to identify the most popularly documented digital sectors in this context, which include the Internet of Things (IoT), healthcare, supply chain management, and government sectors. For each sector, this review documents use cases in which an attempt is made to implement blockchain solutions. The main purpose of this paper is to probe each sector for the growing maturity of blockchain technology and to document the unique benefits and challenges arising from the use of this technology. The findings show that despite the growing reputation of blockchain technology, its implementation within these four sectors remains in infancy because the use cases lack concrete evaluations of its effectiveness and plausibility. Nevertheless, the categorization of current blockchain use cases demonstrates current applications and sector-specific concerns that suggest future directions for further research.

Blockchain Use Cases in Digital Sectors: A Review of the Literature

Enhancing Precision Agriculture: A Comprehensive Review of Machine Learning and AI Vision Applications in All-Terrain Vehicle for Farm Automation

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 problems, this paper proposed and developed novel methods that can 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. To curb theft of grain at storage points, the system used motion sensing through the use of PIR sensors, wireless radio communication module and the GSM/GPRS technologies such that when anyone comes in the range of PIR sensor, then the sensor will send a logic signal to the microcontroller. Lastly, the RFID combined with GSM and Arduino microcontroller responsible for grain tracking. From the results obtained in the experiment conducted it is believed that once this technology is adopted, theft will be reduced and grain management in the FRA satellite Depots dotted around the country will improve.

/pdf/an-iot-based-warehouse-intrusion-detection-e-perimeter-and-jofqkksksg.pdf

An IoT based Warehouse Intrusion Detection(E-Perimeter) and Grain Tracking Model for Food Reserve Agency

In order to introduce modern warehousing, improve upon the storage of grain and grain marketing business processes for the Food Reserve Agency in Zambia, a prototype of a remote sensor network was developed and built as a proof of concept for a much wider deployment using cloud computing and the internet of things concept. It was determined that a wireless sensor network would aid the Food Reserve Agency in analytics, timely action and real-time reporting from all its food depots spread-out throughout Zambia. Google’s Android Things Platform was used in order to achieve the objectives. Advantages of Android Things over traditional platforms that have been used to develop wireless sensor networks were looked into and presented in this paper.

/pdf/a-remote-sensor-network-using-android-things-and-cloud-50rdsdc8lf.pdf

A Remote Sensor Network using Android Things and Cloud Computing for the Food Reserve Agency in Zambia

E-government has been an essential part of the targets set forth by all governments that are signatory to the United Nations 2030 sustainable development goals which am to create effective, accountable and inclusive governments. In order to achieve e-government in the most efficient manner, more and more governments around the world are embracing cloud storage and cloud applications as the de facto standard for data storage, archiving, analysis and manipulation. The amounts of money that governments will spend are huge and the infrastructure requirements far exceed the capabilities of most government institutions. Models such as centralized management of cloud infrastructure have been adopted but this defeats the purpose of cloud computing where resources and even management of those resources are decentralized. In this paper we present a proposal for a standard model for governments to utilize their existing or planned cloud infrastructure and leverage private and public cloud infrastructure in order to achieve true cloud decentralization. We propose that Blockchain technologies provide the most optimal and quickest methods towards e-government. We look into the problem of analyzing big data in national data centres and methods of optimization based on already available technology.

/pdf/blockchain-it-s-practical-use-for-national-data-centres-2sg24lyvkx.pdf

Blockchain – it’s practical use for National Data Centres

To achieve true artificial intelligence would be to mimic the human brain. Some have espoused that current systems that we call AI today are nothing more than if-else statements. There are other arguments that state that indeed, the act of decision making itself is a bunch of nested if-else statements. However, we note that the human brain and through processes that are far more complicated than that has levels of cognition that far outweigh those of any machines that have been made today. While computing systems perform better at certain tasks than human beings do, they remain inherently specific. Human minds are generally creative and knowledge making entities. In this paper, we explore the current progress made towards achieving Artificial General Intelligence and look at it from the angle of Hyperdimensional Computing and Vector Symbolic Architectures both running with the power of quantum computing. We explain how the achievement of AGI will lead to a much more sustainable form of industrial development as has been touted through advancements towards the Fourth Industrial Revolution.

Towards Artificial General Intelligence - A Survey of Hyperdimensional Computing and Vector Symbolic Architectures with Quantum Computing for Multivariate Predictions

The use of Artificial Intelligence in agriculture is a novel approach that promises many benefits. Notable is the emphasis by nations of the world to end hunger by 2030 as enshrined in Sustainable Development Goal number 2[1]. To end world hunger, the fundamental ways of doing things in and around the agricultural space will have to change by adopting much more sustainable models and relooking at the supply chain system with the space. For example, it is noted that more food goes to waste through spoilage than is required to feed all the hungry on earth. While in other parts of the globe, the food supply would be sufficient were it not for the stock that spoils due to pests and diseases. It the goal of this paper to provide a possible solution for the second scenario on spoilage due to pests and diseases by adopting Artificial Intelligence approaches such as Machine Learning and tweaking existing methods by improving the overall prediction score. We provide areas of interest that may be considered and show that further research in the subject may yield positive results in the field of Predictive Analysis as concerns the field of agriculture. A Systematic Review is done on over 20 pieces of literature around the field of Predictive analysis and notable gaps are highlighted while areas of possible improvement are also indicated. It is then against this backdrop that the highlighted areas of improvement may later be tested in subsequent work.

Current Trends in Machine-Based Predictive Analysis in Agriculture for Better Crop Management - A Systematic Review

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Papers

A Remote Sensor Network using Android Things and Cloud Computing for the Food Reserve Agency in Zambia

Blockchain – it’s practical use for National Data Centres

Towards Artificial General Intelligence - A Survey of Hyperdimensional Computing and Vector Symbolic Architectures with Quantum Computing for Multivariate Predictions

Current Trends in Machine-Based Predictive Analysis in Agriculture for Better Crop Management - A Systematic Review